6 Unsupervised Learning Jobs nearby Meerut

Role Overview: You will be responsible for leveraging your 3+ years of experience in Data Science, machine learning, or related fields to tackle structured and unstructured data problems. Your expertise in Machine Learning and Statistics will be crucial as you develop, implement, and deploy machine learning models on cloud platforms such as Azure, AWS, and GCP. Your role will involve integrating machine learning models into existing systems, developing MLOps pipelines, monitoring model performance, and providing insights to stakeholders. Key Responsibilities: - Apply practical experience in time series forecasting, clustering, classification techniques, regression, boosting algorithms, optimization techniques, NLP, and recommendation systems - Utilize programming skills in Python/PySpark and SQL to develop and implement machine learning models - Deploy machine learning models on cloud platforms using AWS/Azure Machine Learning, Databricks, or other relevant services - Integrate machine learning models into systems and applications to ensure seamless functionality and data flow - Develop and maintain MLOps pipelines for automated model training, testing, deployment, and monitoring - Monitor and analyze model performance, providing reports and insights to stakeholders - Demonstrate excellent written and verbal communication skills in presenting ideas and findings to stakeholders Qualification Required: - Engineering Graduate from a reputed institute and/or Masters in Statistics, MBA - 3+ years of experience in Data Science - Strong expertise in machine learning with a deep understanding of SQL & Python - Exposure to industry-specific (CPG, Manufacturing) use cases - Strong client-facing skills - Organized and detail-oriented with excellent communication and interpersonal skills About the Company: Polestar Solutions is a data analytics and enterprise planning powerhouse that helps customers derive sophisticated insights from data in a value-oriented manner. With a presence in the United States, UK, and India, Polestar Solutions boasts a world-class team and offers growth and learning opportunities to its employees. The company has been recognized for its expertise and passion in various accolades, including being featured in the Top 50 Companies for Data Scientists and as Financial Times" High-Growth Companies across Asia-Pacific. (Note: The job description did not provide additional details about the company.),

Role Overview: You have over 3 years of experience in Machine Learning (ML) and Artificial Intelligence (AI), showcasing a successful track record of leading and implementing complex ML and AI projects. Your expertise spans a deep understanding of ML and AI concepts, algorithms, and techniques, covering supervised and unsupervised learning, reinforcement learning, and neural networks. Proficiency in programming languages like Python, R, or Scala, as well as utilizing ML and AI libraries such as TensorFlow, PyTorch, and scikit-learn, is essential. You have hands-on experience in applying ML and AI solutions to tackle real-world challenges in areas like recommendation systems, fraud detection, natural language processing, and computer vision. Your knowledge of data engineering principles and managing large-scale datasets is commendable. Key Responsibilities: - Lead and execute complex ML and AI projects effectively. - Motivate and manage a team of data scientists and engineers to achieve project goals. - Translate business requirements into ML and AI solutions and communicate technical concepts to non-technical stakeholders. - Think strategically, drive innovation, and solve problems analytically within the organization. - Collaborate with various stakeholders utilizing excellent communication, presentation, and interpersonal skills. Qualifications: - Bachelor's or Master's degree in Computer Science, Data Science, or a related field is mandatory. - A Ph.D. is considered advantageous for this role.,

You will be working as a Research Engineer-II at Attentive.ai, contributing to the development of intelligent systems for automated construction take-off and estimation through cutting-edge deep learning, computer vision, and NLP technologies. Your role will involve supporting the end-to-end lifecycle of AI-based solutions, impacting the scalability, accuracy, and efficiency of products directly. **Roles & Responsibilities:** - Contribute to research and development initiatives focusing on Computer Vision, Image Processing, and Deep Learning in construction-related data. - Build and optimize models for extracting insights from documents like blueprints, scanned PDFs, and SVG files. - Aid in the development of multi-modal models integrating vision with language-based features such as NLP/LLMs. - Follow best practices in data science and machine learning, including data-centric development, experiment tracking, model validation, and reproducibility. - Collaborate with cross-functional teams to translate research ideas into real-world applications. - Write clean, scalable, and production-ready code using Python and frameworks like PyTorch, TensorFlow, or HuggingFace. - Stay updated with the latest research in computer vision and machine learning and assess applicability to construction industry challenges. **Skills & Requirements:** - 3-5 years of experience in applied AI/ML and research with a strong emphasis on Computer Vision and Deep Learning. - Proficient in image processing, visual document understanding, and feature extraction from visual data. - Familiarity with SVG graphics, NLP, or LLM-based architectures is a plus. - Deep understanding of unsupervised learning techniques like clustering, dimensionality reduction, and representation learning. - Proficiency in Python and ML frameworks such as PyTorch, OpenCV, TensorFlow, and HuggingFace Transformers. - Hands-on experience with model optimization techniques (e.g., quantization, pruning, knowledge distillation) is beneficial. - Experience with version control systems, project tracking tools, and cloud environments. - Familiarity with Docker, Kubernetes, and containerized ML deployment pipelines. - Strong analytical and problem-solving skills with a passion for building innovative solutions; ability to rapidly prototype and iterate. - Comfortable working in a fast-paced, agile, startup-like environment with excellent communication and collaboration skills. You will have the opportunity to work in a visionary team at Attentive.ai, developing a groundbreaking AI solution for the construction industry. Additionally, you will gain exposure to real-world AI deployment and cutting-edge research in vision and multimodal learning. The company culture encourages ownership, innovation, and growth, providing opportunities for fast learning, mentorship, and career progression.,

As an experienced and dynamic Associate Lead with 6+ years of experience in Machine Learning (ML) and Artificial Intelligence (AI), you will be leading our ML and AI team. Your role as the Manager of ML and AI involves driving the development and implementation of strategies and initiatives in these areas. You will oversee a team of talented data scientists and engineers, fostering innovation and delivering cutting-edge solutions in ML and AI. **Responsibilities:** - Lead and manage the ML and AI team, providing technical guidance, mentorship, and performance management. - Define and execute the ML and AI strategy, aligning it with business objectives and market trends. - Collaborate with cross-functional teams to identify and prioritize ML and AI opportunities that drive business value. - Stay updated with the latest advancements in ML and AI technologies, tools, and algorithms, and identify potential applications in the organization. - Oversee the design, development, and deployment of ML and AI models, ensuring scalability, efficiency, and accuracy. - Provide expertise in areas such as predictive modeling, natural language processing, computer vision, and deep learning. - Collaborate with data engineering teams to ensure effective data collection, preprocessing, and feature engineering for ML and AI projects. - Establish and maintain best practices for data governance, model evaluation, and performance monitoring. - Manage and prioritize multiple ML and AI projects, ensuring timely delivery and adherence to quality standards. - Work closely with stakeholders to understand their requirements, communicate ML and AI capabilities, and drive adoption and implementation. - Stay abreast of regulatory and ethical considerations in ML and AI, ensuring compliance and responsible use of data. **Requirements:** - 10+ years of experience in ML and AI, with a strong track record of leading and delivering complex projects in these domains. - In-depth knowledge of ML and AI concepts, algorithms, and techniques, including supervised and unsupervised learning, reinforcement learning, and neural networks. - Proficiency in programming languages such as Python, R, or Scala, along with ML and AI libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Experience in applying ML and AI techniques to solve real-world problems in areas such as recommendation systems, fraud detection, natural language processing, or computer vision. - Strong understanding of data engineering principles and experience working with large-scale datasets. - Excellent leadership and people management skills, with the ability to motivate and inspire a team of data scientists and engineers. - Proven ability to translate business requirements into ML and AI solutions and effectively communicate technical concepts to non-technical stakeholders. - Strong analytical and problem-solving skills, with the ability to think strategically and drive innovation. - Excellent communication, presentation, and interpersonal skills. **Minimum Qualification:** - Bachelor's or Master's degree in Computer Science, Data Science, or a related field. A Ph.D. is a plus.,

As an experienced AI/ML Solution Architect at our company, you will play a crucial role in designing and delivering enterprise-grade Machine Learning and Generative AI solutions. Your responsibilities will involve defining scalable architectures, collaborating with various teams, and providing technical leadership. Here's a breakdown of what to expect: **Key Responsibilities:** - Define and own end-to-end AI/ML architecture, covering data pipelines to production deployment. - Evaluate and select ML frameworks, tools, and platforms for scalability, cost-efficiency, and maintainability. - Design feature stores, data pipelines, and inference services for real-time and batch ML workloads. - Establish best practices for model governance, versioning, and reproducibility. - Lead LLM integration with business applications using LangChain, LangGraph, and related frameworks. - Provide technical leadership, mentorship, and roadmap alignment for engineering and data science teams. **Key Skills & Competencies:** - Expertise in Python, FastAPI, and PySpark for large-scale data engineering. - Strong grounding in various ML algorithms: supervised, unsupervised, and reinforcement learning. - Proficiency with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. - Hands-on experience in LLM orchestration frameworks like LangChain, LlamaIndex, LangGraph, and LangFlow. - Experience in MLOps and cloud AI platforms like AWS SageMaker, Azure ML, and GCP Vertex AI. - Deep understanding of prompt engineering, Agentic AI, and retrieval-augmented generation (RAG). - Familiarity with SQL/NoSQL databases and scalable data infrastructure. **Mandatory AI/ML Packages:** - scikit-learn, XGBoost, LightGBM, CatBoost - TensorFlow, Torch, TorchVision, Keras - Pandas, NumPy, PySpark, Dask, Polars - MLflow, SageMaker, FastAPI, Flask, Uvicorn, AioHTTP - SQLAlchemy, PyMongo, Boto3, Redis - Matplotlib, Seaborn, Plotly, YData-Profiling - LangChain, LlamaIndex, LangGraph, LangFlow, Transformers This job opportunity is with TechAhead, a global digital transformation company known for its AI-first product design thinking and bespoke development solutions. With over 15 years of experience, TechAhead has partnered with Fortune 500 companies and leading global brands to drive digital innovation and excellence. Join us to shape the future of digital innovation worldwide and drive impactful results with cutting-edge AI tools and strategies!,

As a Senior Software Tester (RPA, AI / ML) at SynapseIndia, your role will involve the following responsibilities: - Design, develop, and execute test plans, test cases, and test scripts for RPA, AI, and ML-based projects. - Validate business workflows automated using RPA tools such as UiPath, Automation Anywhere, Blue Prism, etc. - Test ML models for accuracy, precision, recall, and robustness across various datasets. - Perform functional, regression, integration, system, and performance testing for AI/ML applications. - Collaborate closely with developers, data scientists, and business analysts to understand requirements and identify potential test scenarios. - Ensure AI/ML systems handle edge cases, anomalies, and exceptions effectively. - Automate test scripts where feasible using tools/frameworks like Selenium, PyTest, Robot Framework, etc. - Document bugs, errors, and inconsistencies, and track them to closure. - Participate in code reviews and provide quality feedback. - Stay updated with advancements in AI/ML testing techniques and RPA platforms. Qualifications and skills required for this role include: - Bachelor's degree in Computer Science, Information Technology, or a related field. - 3+ years of experience in software testing, with exposure to AI/ML and RPA projects. - Strong understanding of QA methodologies, SDLC, and STLC. - Hands-on experience with RPA tools such as UiPath, Automation Anywhere, Blue Prism. - Knowledge of AI/ML concepts such as supervised/unsupervised learning, NLP, computer vision, and model evaluation metrics. - Experience with testing APIs, data pipelines, and AI models. - Familiarity with Python, SQL, or scripting languages for data validation and test automation. - Experience with test management tools like JIRA, TestRail, Zephyr, etc. - Good analytical, problem-solving, and communication skills. - Exposure to cloud platforms such as AWS, Azure, GCP, and their AI/ML services. - Experience in testing chatbots, AI assistants, or predictive analytics applications. - Basic understanding of MLOps and continuous testing practices. - ISTQB or similar certification.,

Role Overview: You will be joining the Data Science and AI/ML team that collaborates across the organization to develop and deliver AI and ML powered software solutions aimed at improving patient outcomes, satisfying partners and customers, and enhancing business operations in an AI First manner. Your role as a Sr. Mgr. for Machine Learning Engineering will involve leading the development of ML architecture and operations, managing the AI operations team, ensuring production-grade AI/ML systems, and fostering best coding practices within the team. Key Responsibilities: - Drive a culture of learning within your team and challenge the status quo - Mentor and lead a team of engineers to help them grow - Collaborate with senior technology stakeholders to make key technology decisions - Grow and mentor talent to build a world-class development culture - Work closely with stakeholders to create impactful AI/ML features and products - Lead and develop a team of ML engineers to execute the AI/ML roadmap - Develop and optimize departmental processes to enhance team performance - Lead AI/ML model development, deployment, implementation, and monitoring - Collaborate with Data Scientists and Data Engineers, owning the end-to-end process - Build and maintain global AI/ML architectures and provide production support - Document model & ML system design, experiments, tests, validations, and live metrics - Stay updated on industry trends and leverage best practices for successful AI/ML solutions - Implement internal process improvements and build capabilities for production-level AI/ML systems - Support stakeholders with AI/ML-related technical issues and infrastructure needs - Handle escalated incidents and suggest solutions for future prevention - Participate in Code Review and process improvement Qualification Required: - 8+ years of industry experience in Machine Learning Engineering, Data Science, or Data Engineering - M.S or PhD in Data Science/Machine Learning or related areas like Computer Science, Operations Research, Applied Statistics, and Biomedical Informatics - Experience managing Data Science, Machine Learning, and/or AI teams - Strong leadership experience in AI/ML programs, development processes, and mentoring - Proficiency in developing data analytics systems, including model building, performance evaluation, and online deployment - Experience building scalable AI/ML systems for various advanced AI/ML problems - Knowledge of handling large and distributed datasets on various platforms - Familiarity with AWS or other cloud-based tools for data processing, model development, deployment, and monitoring - Strong mathematical foundation for Data Science, including probability, statistics, optimization, and linear algebra - Expertise in machine learning techniques such as regression, classification, clustering, time series forecasting, and optimization methods Note: Joining this team means being part of a culture that focuses on excellence, diversity, and inclusivity, encouraging individual expression and innovative ideas. If you are ready to contribute to making the world a healthier place and thrive in a challenging and supportive environment, apply now!,

As an AI Developer at vConstruct's Data Science & Analytics team, you will play a crucial role in expanding the Generative AI capability. Your primary responsibility will be to design, build, and deploy production-ready solutions using large language models (LLMs), multimodal models, and classic ML techniques. You will collaborate with AI Engineers, Data Scientists, and Analysts to revolutionize the construction lifecycle through automation and data-driven insights. Key Responsibilities: - Prototyping: Collaborate with experts to frame GenAI use cases and develop quick LLM-based tools. - Modeling: Fine-tune and prompt models, utilizing ML/DS when GenAI is not the ideal solution. - Engineering: Deploy models as scalable Azure services using CI/CD practices. - Collaboration: Work closely with cross-functional teams, document solutions, and conduct demos. - Learning: Stay updated on GenAI trends and share knowledge internally. Qualifications Required: - Education: B.E./B.Tech or M.S. in Computer Science, Data Science, AI/ML, or related field. - Experience: Approximately 5 years of experience delivering production software or ML solutions, with at least 2 years of hands-on experience with LLMs or other Gen AI models. - Programming: Proficiency in Python (FastAPI / LangChain / LangGraph), familiarity with TypeScript or C# is a plus. - Gen AI Tooling: Experience with OpenAI/Azure OpenAI SDKs, embeddings, and vector databases (e.g., Azure Cognitive Search, Pinecone, FAISS). - ML Fundamentals: Strong understanding of supervised/unsupervised learning, evaluation metrics, and experiment tracking tools like MLflow and Weights & Biases. - Cloud & DevOps: Comfortable with deploying on Azure, writing Dockerfiles, and setting up pipelines using Azure DevOps/GitHub Actions. - Data Handling: Proficient in SQL and Pandas, capable of handling various data types including tabular, text, image, and BIM/IFC data. - Soft Skills: Clear communicator with the ability to explain complex ideas to non-technical stakeholders, excels in fast-paced, iterative environments. Nice to Have: - Knowledge of construction, engineering, manufacturing, or related domains. - Frontend skills (React, Streamlit) for developing user-facing Gen AI tools. - Familiarity with Snowflake, Power BI, or Tableau for analytics and visualization. vConstruct specializes in providing high-quality Building Information Modeling and Construction Technology services for construction projects. It is a subsidiary of DPR Construction, a national commercial general contractor known for technically challenging and sustainable projects in various markets. For more information, please visit www.vconstruct.com.,

As an AI / GenAI Retail Specialist Manager at S&C Global Network, you will be responsible for leading the development and implementation of artificial intelligence solutions across retail operations. Your role will require a strong blend of technical expertise, domain knowledge in the retail sector, and leadership capabilities to drive impactful AI and GenAI initiatives. Your expertise in AI will be crucial in developing cutting-edge solutions that enhance retail performance in areas such as merchandising, pricing, customer engagement, and product assortment. **Key Responsibilities:** - Utilize your deep understanding of the retail industry to design AI solutions addressing critical retail business needs. - Supervise teams in building, validating, and deploying ML/DL models using frameworks such as TensorFlow, PyTorch, and Hugging Face. - Develop and oversee the implementation of GenAI-powered tools. - Design, develop, and implement AI algorithms and generative models tailored to the retail sector. - Focus on creating AI models for various use cases like customer lifecycle, personalized customer experiences, pricing optimization, and product assortment. - Translate data insights into actionable strategies for marketing, merchandising, and customer experience teams. - Collaborate with cross-functional teams to understand retail business challenges and provide AI-driven solutions. - Communicate the potential of AI solutions to technical and non-technical stakeholders, ensuring alignment with business objectives. **Qualifications Required:** - Proven experience in supervised and unsupervised learning, deep learning, and generative AI models. - Expertise in machine learning, NLP, and generative AI models. - Hands-on experience with platforms like TensorFlow, PyTorch, and OpenAI technologies. - Knowledge of AI ethics and responsible AI practices. - Experience with cloud platforms and modern MLOps practices. The company, Accenture, is seeking a candidate with 6-10 years of relevant experience in data science, machine learning, or AI, with at least 2+ years in a leadership or managerial role. Educational qualifications include MSc. Statistics, B.Tech./M.Tech in Computer Science, Econometrics, or Data Science. Retail tech experience in e-commerce, fashion, grocery, or quick-commerce segments is preferred. Knowledge of ethical AI practices, responsible AI governance, and working with APIs of commercial LLMs is desirable.,

As a senior data scientist at UBS, you will play a pivotal role in driving digital transformation by working on data science projects within the newly established Data and Analytics Team in Group Legal. Your responsibilities will include: - Collaborating with various stakeholders to translate reporting requirements into actionable tasks and implement product enhancements. - Designing, building, and deploying high-performance AI/ML/NLP models to meet business objectives. - Monitoring and optimizing model performance to ensure quality, stability, and scalability. - Cleaning, manipulating, and processing raw data into useful information suitable for business purposes. - Validating AI/ML opportunities, defining business cases, and creating roadmaps for implementation. - Documenting model performance, governance, and validation processes comprehensively. - Mentoring and guiding junior data scientists and analysts to foster technical excellence across the team. To excel in this role, you should possess the following qualifications: - Minimum of 3 years of experience delivering data science projects in a leading consultancy or at a large organization. - Proficiency in developing end-to-end ML and NLP solutions, including data sourcing, feature engineering, model training, evaluation, and visualization. - Experience in state-of-the-art ML algorithms and techniques, such as XGBoost, Neural Networks, supervised, unsupervised, or reinforcement learning. - Proficiency in building ML & NLP / LLM solutions using common ML libraries and frameworks like Pandas, Sklearn, TensorFlow, Transformers, OpenAI, Huggingface. - Hands-on experience with NLP applications such as named entity recognition, text classification, sentiment analysis, or chatbot development. - Familiarity with MLOps practices, containerized solutions like Docker, Kubernetes, and cloud platforms such as Azure, AWS, or Google Cloud. - Ability to explain technical concepts to non-technical stakeholders. - Strong team player and communicator. UBS is the world's largest and the only truly global wealth manager, operating through four business divisions: Global Wealth Management, Personal & Corporate Banking, Asset Management, and the Investment Bank. With a presence in over 50 countries, UBS offers flexible ways of working and a purpose-led culture that fosters collaboration and innovation. UBS is an Equal Opportunity Employer that values diversity and empowers individuals from various backgrounds. If you are looking to make an impact and be part of a dynamic team, consider joining #teamUBS. UBS welcomes applications from career returners. Learn more about the Career Comeback program on ubs.com/careercomeback.,

As a Machine Learning Intern at Epimove, you will contribute to the development and fine-tuning of machine learning models, focusing on deep learning and segmentation tasks. You will collaborate with the team to implement solutions that align with business goals. Your responsibilities will include: - Assist in designing, training, and evaluating machine learning models, with a focus on deep learning and segmentation techniques. - Fine-tune existing models to improve accuracy and performance. - Prepare and process datasets to train machine learning models effectively. - Work on segmentation and classification problems to derive insights from complex data. - Collaborate with the team to implement solutions in real-world applications. - Stay updated with the latest advancements in machine learning and deep learning domains. To excel in this role, you should have the following qualifications: - Strong understanding of machine learning algorithms, deep learning frameworks, and Python programming. - Familiarity with machine learning libraries like PyTorch. - Experience in fine-tuning pre-trained models and enhancing their performance. - Practical knowledge of segmentation techniques in both supervised and unsupervised learning. - Ability to handle large datasets, conduct feature engineering, and solve problems efficiently. - Excellent communication skills for remote collaboration. - Capacity to work independently, manage multiple tasks, and prioritize effectively. - Pursuing or recently completed a degree in Computer Science, Machine Learning, Data Science, or a related field. Preferred skills that would be beneficial for this role include knowledge of NLP or Computer Vision tasks. Epimove offers a hands-on experience with advanced machine learning technologies, an innovative remote work environment, opportunities to contribute to impactful projects, and the chance to learn from industry experts while building a career in AI.,

Role Overview: As a back-end engineer at Google, you will be utilizing your expertise in Machine Learning to combat abuse and ensure user safety. Your role will involve collaborating with domain expert analysts to set up data pipelines, develop machine learning models, and enhance automated review and detection systems. You will also work on integrating online/offline systems with various Google platforms to gather signals, features, and verdicts. Additionally, you will lead projects across different teams within the organization, providing guidance on solutions and execution. Key Responsibilities: - Utilize Machine Learning knowledge to combat abuse and enhance user safety. - Perform integrations with various Google systems for signal gathering and feature extraction. - Collaborate with domain expert analysts to set up data pipelines and machine learning models. - Develop and improve automated review and detection models. - Lead projects across different teams, providing guidance on solutions and execution strategies. Qualifications Required: - Bachelor's degree or equivalent practical experience. - 5 years of experience in software development with expertise in one or more programming languages, data structures, or algorithms. - 3 years of experience with Machine Learning/Artificial Intelligence algorithms and tools, or natural language processing. - 3 years of experience in testing, maintaining, or launching software products. - 1 year of experience in software design and architecture. - Experience with machine learning concepts such as supervised and unsupervised learning, clustering, anomaly detection, and Large Language Model fine-tuning. - Proficiency in data analysis and Machine Learning frameworks like Numpy, Scikit-learn, pandas, SQL, or Matplotlib. - Proficiency in C++ or Python. - Knowledge of fundamental computer science concepts and Google infrastructure or Google Cloud Platform (GCP), including databases, operating systems, algorithms, and Machine Learning.,

As a Machine Learning Instructor at MIT Academy SDN BHD, you will play a vital role in educating and mentoring students in the field of machine learning and artificial intelligence. Your passion for teaching and strong technical expertise will be essential in delivering engaging lectures, guiding students through real-world projects, and staying updated with industry trends. Key Responsibilities: - Design, develop, and deliver engaging lectures, labs, and projects in Machine Learning and related topics. - Teach core concepts such as supervised and unsupervised learning, neural networks, natural language processing, computer vision, and model deployment. - Guide students through real-world projects, case studies, and capstone assignments. - Stay updated with the latest industry trends and incorporate them into teaching content. - Mentor students in career paths, research opportunities, and skill development. - Collaborate with other faculty to enhance the curriculum and learning outcomes. Required Qualifications: - Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or related field (PhD preferred). - Minimum 2 years of teaching or industry experience in Machine Learning / AI. - Strong programming skills in Python and familiarity with ML libraries (TensorFlow, PyTorch, Scikit-learn, etc.). - Experience with data visualization, feature engineering, and model optimization. - Excellent communication and presentation skills. - Passion for teaching and mentoring students. Preferred Qualifications: - Industry certifications in AI/ML (e.g., TensorFlow Developer, AWS Machine Learning, etc.). - Experience with cloud platforms (AWS, GCP, Azure). - Prior experience teaching or mentoring in an educational institution. - Contribution to open-source ML projects or published research papers. In addition to the challenging and rewarding role of a Machine Learning Instructor, you will benefit from: - Competitive salary and benefits package. - Opportunity to work in a collaborative academic environment. - Access to modern labs, tools, and industry projects. - Professional growth through workshops, seminars, and research opportunities.,

Job Description: Role Overview: Join the ML engineering team to explore cutting-edge machine learning technologies, develop scalable AI solutions, and contribute to real-world applications. This collaborative learning opportunity focuses on end-to-end ML pipeline development, model deployment, and production system optimization. Key Responsibilities: - Design, develop, and optimize machine learning models using Python, TensorFlow, PyTorch, and scikit-learn frameworks - Build and maintain robust ML pipelines from data preprocessing through model deployment and monitoring - Conduct data analysis, feature engineering, and statistical validation to ensure high-quality model performance - Implement model evaluation frameworks and A/B testing infrastructure for continuous improvement - Collaborate with cross-functional teams including data scientists, software engineers, and product managers - Deploy ML models to production environments using Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure) - Participate in code reviews, technical discussions, and contribute to research publications when applicable Qualification Required: Must-Haves: - Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or related field (final year students or recent graduates) - Strong programming proficiency in Python with experience in NumPy, Pandas, and machine learning libraries - Solid understanding of machine learning algorithms including supervised/unsupervised learning, neural networks, and deep learning - Knowledge of data structures, algorithms, and software engineering best practices - Experience with version control systems (Git) and collaborative development workflows Nice-to-Haves: - Hands-on experience with deep learning frameworks like TensorFlow, PyTorch, or Keras - Familiarity with MLOps practices, model deployment, and production monitoring systems - Understanding of computer vision, natural language processing, or reinforcement learning applications - Experience with cloud-based ML services and containerization technologies - Previous internship experience or significant open-source contributions in ML/AI projects Additional Details: This unpaid internship offers a collaborative knowledge-sharing opportunity in the rapidly expanding field of machine learning engineering. Outstanding performers will be considered for full-time positions based on technical excellence, problem-solving abilities, and demonstrated impact on ML system development. Duration: 6 months Hours: 09:00 AM to 06:00 PM (Monday to Friday) Location: Ganesh Glory 11, Jagatpur, Ahmedabad, 382470 (Offline Internship),

Role Overview: Machine learning (ML) is a subfield of artificial intelligence that focuses on developing algorithms to learn from data, identify patterns, and make predictions or decisions without explicit programming. It enables systems to improve their performance on specific tasks by adjusting their behavior based on the data they are exposed to. Key Responsibilities: - Learning from Data: Train machine learning algorithms on large datasets to identify patterns and relationships within the data. - No Explicit Programming: ML algorithms learn from data and adapt their behavior instead of relying on traditional programming methods. - Prediction and Decision Making: Enable systems to make accurate predictions or decisions based on the patterns learned through machine learning. - Adaptability and Improvement: ML models can enhance their performance and accuracy over time as they are exposed to more data. Qualifications Required: - Experience with supervised learning, unsupervised learning, and reinforcement learning algorithms. - Proficient in analyzing data and identifying patterns. - Strong problem-solving skills and ability to make decisions based on data analysis. [Note: No additional details of the company were provided in the job description.],

As an ML Engineer at Aaptatt, your role involves developing, optimizing, and maintaining end-to-end ML solutions. This includes working on data pipelines, model training, and deployment. You will collaborate with stakeholders to translate business requirements into scalable, production-ready ML applications. Additionally, you will apply advanced ML techniques such as supervised learning, unsupervised learning, NLP, CV, and time-series analysis using Python and key data science libraries. It is crucial to ensure model performance, accuracy, and maintain clear technical documentation and code standards. Qualifications Required: - Proficiency in Python programming language - Experience in developing and deploying ML models - Strong understanding of machine learning concepts and algorithms - Ability to work collaboratively with stakeholders to meet business requirements About the Company: Aaptatt is a universal company with a focus on cloud and DevOps services. With a track record of 4 years, our team prides itself on delivering projects on time while maintaining the highest standards of quality.,

Role Overview: You are a skilled Data Scientist with expertise in machine learning, statistical modeling, and business-focused analytics. Your role involves building predictive models, time-series forecasting, and optimization solutions using Python, SQL, and Azure ML or Databricks. Strong communication skills are essential to translate complex data into clear business insights. Key Responsibilities: - Analyze large, complex datasets to uncover actionable insights for driving business impact. - Design and implement predictive models, especially in areas like customer penetration optimization and regional performance forecasting. - Apply machine learning techniques (supervised and unsupervised learning) to solve critical business problems such as classification, regression, and clustering. - Engineer meaningful features from raw data to optimize model performance. - Conduct exploratory data analysis (EDA) to identify trends, anomalies, and business opportunities. - Conduct feature selection and hyperparameter tuning to enhance model performance. - Validate model results using appropriate statistical and ML evaluation metrics. - Collaborate with data engineers to build and refine robust data pipelines. - Translate insights into clear, actionable strategies by working closely with product, engineering, and business teams. - Utilize visualization tools like Tableau, Power BI, and Google Analytics to communicate insights and model outcomes. - Build models for production deployment using tools like Spring Boot and GitLab. - Consider partner-specific (JV & Wholesale) and regional variations to fine-tune analytics approaches. - Stay updated with ML/AI innovations and suggest tool or process improvements. - Participate in Agile ceremonies and manage tasks using tools such as Jira. - Document methodologies and maintain version control for all modeling projects. Qualification Required: - Bachelor's degree in Computer Science or a related field. - Master's degree or equivalent advanced degree preferred. - Proven track record of delivering data science projects from ideation to production. - Strong communication skills and the ability to tell compelling stories with data. - Comfortable working with both structured and unstructured data sets. Additional Company Details: GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world's largest and most forward-thinking companies. Since 2000, GlobalLogic has been pioneering the digital revolution by creating innovative and widely used digital products and experiences. The company collaborates with clients to transform businesses and redefine industries through intelligent products, platforms, and services. GlobalLogic prioritizes a culture of caring, continuous learning and development, interesting and meaningful work, balance and flexibility, and integrity as key values for employees and clients.,

As a Senior Engineer/Lead Senior Engineer in Data Analytics and ML Model Development, you will be part of a dedicated team that applies cutting-edge AI and ML technologies to address complex challenges in chip design, qualification, and debug engineering processes. The primary goal is to improve engineering efficiency by implementing intelligent automation, leveraging data-driven insights, and creating innovative tools. **Key Responsibilities:** - Design and implement comprehensive data analytics workflows tailored for semiconductor engineering applications. - Develop, train, and optimize ML models using various techniques including supervised, unsupervised, and deep learning. - Conduct feature engineering, model evaluation, and hyperparameter tuning to enhance model performance. - Build scalable data pipelines for ingestion and transformation using Python and cloud-native tools. - Utilize statistical analysis and visualization methods to extract valuable insights from extensive datasets. - Perform time series analysis employing techniques like ANOVA and other statistical methods. - Explore GenAI platforms, LLMs, and RAG techniques to enhance model capabilities. - Collaborate with cross-functional teams to integrate ML models into engineering workflows and tools. - Document methodologies and offer technical guidance to internal teams. **Qualifications Required:** - Master's degree in Computer Science, Data Science, or a related field. - Proficient in programming with Python or C++. - Strong grasp of data structures, algorithms, and software design principles. - Excellent analytical and problem-solving skills. - Hands-on experience with supervised and unsupervised learning techniques. - Familiarity with deep neural network architectures such as RNNs and Transformers. - Proficiency with ML frameworks like scikit-learn, TensorFlow, or PyTorch. - Knowledge in GenAI, LLMs, and RAG Optimization, as well as LLM Finetuning and Distillation. - Skilled in data analysis using Pandas, NumPy, and Matplotlib. - Understanding of statistical analysis, visualization, feature engineering, and model evaluation. - Knowledge of GPU, CUDA, and high-performance computing frameworks and methods. **Additional Company Details:** The company offers benefits such as food provision, health insurance, internet reimbursement, life insurance, paid time off, and provident fund. This is a full-time, permanent position requiring in-person work. Ensure you have a Master's degree in Computer Science, Data Science, or a related field with at least 2 years of experience in machine learning. If you have a Ph.D. or extensive experience in large model development and training from scratch, familiarity with time series analysis, SQL databases, ETL frameworks, cloud platforms, LLM integration frameworks, distributed computing, and cloud-scale data processing, it would be considered a plus. Join our team to contribute to the advancement of chip design and engineering processes through innovative data analytics and machine learning solutions.,

Role Overview: As a Retail Specialized Data Scientist at Level 9 in the SnC GN Data & AI team, you will be responsible for utilizing advanced analytics, machine learning, and statistical modeling techniques to support data-driven decision-making in the retail sector. Your role will involve collaborating with various teams such as marketing, product management, supply chain, and customer insights to drive business strategies and innovations. The ideal candidate should possess experience in retail analytics and demonstrate the ability to transform data into actionable insights. Key Responsibilities: - Leverage Retail Knowledge: Utilize your in-depth understanding of the retail industry, including merchandising, customer behavior, and product lifecycle, to design AI solutions that cater to crucial retail business requirements. - Gather and clean data from diverse retail sources like sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. - Apply machine learning algorithms such as classification, clustering, regression, and deep learning to improve predictive models. - Utilize AI-driven techniques for personalization, demand forecasting, and fraud detection. - Implement advanced statistical methods to optimize existing use cases and develop new products to address emerging challenges and use cases. - Stay abreast of the latest trends in data science and retail technology. - Collaborate effectively with executives, product managers, and marketing teams to translate insights into actionable business strategies. Qualifications Required: - A solid understanding of retail industry dynamics, encompassing key performance indicators (KPIs) like sales trends, customer segmentation, inventory turnover, and promotions. - Strong communication skills to convey complex data insights to non-technical stakeholders, including senior management, marketing, and operational teams. - Attention to detail to ensure data quality, accuracy, and consistency while handling large, complex datasets. - Proficiency in Python for data manipulation, statistical analysis, and machine learning (libraries like Pandas, NumPy, Scikit-learn). - Expertise in supervised and unsupervised learning algorithms. - Minimum 3 years of experience in the field. - Educational background in Data Science, Statistics, Computer Science, Mathematics, or related disciplines. Note: The job description does not include any additional details about the company.,

As a Data Scientist, you will be responsible for building cutting-edge models using NLP, ML, and AI techniques to solve a variety of problems across different domains. Your main tasks will include working closely with the engineering team to deploy models in production, validating the models, and ensuring their effectiveness. - Possess expert-level knowledge in Natural Language Processing, Information Extraction, Scraping, and Text Mining Algorithms. - Strong familiarity with deep learning methods for text analytics. - Proficiency in Machine Learning algorithms such as XGBoost, Linear Regression, Logistic Regression, SVM, Random Forest, Bayesian Methods, Unsupervised Learning, and Reinforcement Learning. - Experience in time series analysis with real-world datasets. - Familiarity with technologies like Flask, FastAPI, and Hug. - Expert Python programmer. - Proven track record of expertise demonstrated through high-quality publications, competitions, or challenges. A minimum qualification of B.E/B.Tech in Computer Science, Electrical Engineering, or EXTC with a solid foundation in mathematics and statistics is necessary. Excellent communication skills, teamwork abilities, and the capacity to thrive in a startup environment are also essential for success in this role. In this role, you will be expected to take care of Text Analytics on Qualitative Customer Feedback and Call Center complaints conversations via Email or Chat. The ideal candidate should have 2 to 8 years of relevant experience, with a salary ranging from 15 Lac to 18 Lac P.A. The industry focus is on Analytics and Business Intelligence.,