397 Machine Learning Jobs in Gurgaon

Location - LTIM Pan IndiaExperience - 5+to 12+ yrsGeneric JD-Mandatory Skills - Data Science, Gen AI, Python, RAG and Azure/AWS/GCP, AI/ML, NLP Secondary - (Any) Machine Learning, Deep Learning, ChatGPT, Langchain, Prompt, vector stores, RAG, llama, Computer vision, Deep learning, Machine learning, OCR, Transformer, regression, forecasting, classification, hyper parameter tunning, MLOps, Inference, Model training, Model DeploymentJD_ More than 6 years of experience in Data Engineering, Data Science and AI / ML domainExcellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc.Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop)Experience in Cloud native skills.Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an assetAnalytical mind and business acumen and Strong math skills (e.g. statistics, algebra)Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable.Experience with NLP, NLG and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc.Great communication and presentation skills. Should have experience in working in a fast-paced team culture.Experience with AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc.Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databasesGood understanding of applied statistics skills, such as distributions, statistical testing, regression, etc.Should be a data-oriented person with analytical mind and business acumen.

Fill below mandatory link.  MLops-virtual interview with Capgemini--all locations, Monday 27th Oct 2025 Fill out form   Position: - Machine Learning Ops Harvest Level: Software Engineer  Job Description:    Machine Learning Ops Engineer is the one whos responsible for managing and optimizing the deployment and operation of machine learning models in production environments. He/she works closely with data scientists, software engineers, and DevOps teams to ensure that machine learning models are integrated seamlessly into existing systems and can scale effectively. Role & Responsibilities Responsible for design and implementation of secure and scalable infrastructure in Azure cloud. Build and maintain CI/CD/CT pipeline across azure cloud platform for Data science projects. Own and automate the infrastructure provisioning, demand forecasting and capacity planning. Build tools and automation to improve systems availability, reliability, performance, monitoring and scalability. Setting up the alerts and monitoring for the platform. Monitoring system, application health, security controls and cost Envision, implement and rollout best MLOPs/DevOps tools and automation.  Requirements: Strong understanding of concepts related to Machine Learning, Architecture, and MLOps practices. Proficient in Azure Cloud practices and managing Azure Kubernetes Service infrastructure. Hands on experience in Python or any other scripting languages (Groovy, Shell) Experience with monitoring tools. Hands-on experience in Docker, Kubernetes. Excellent experience with source code management tools (git) Experience with modern cloud development practices such as Microservices Architecture, REST Interfaces etc. Experience in implementing Data/Model drift. Strive for Continuous Improvement and build continuous integration, continuous development, and constant deployment pipeline. Excellent Troubleshooting skills Always ready to learn more and adopt new cutting-edge technology with right value proposition.  

About ExcelR: ExcelR is a leading edtech company founded by distinguished alumni of IIM and ISB, dedicated to transforming careers through world-class upskilling. Recognized twice with the Deloitte Fast 50 Award, ExcelR is one of Indias fastest-growing tech companies. With an employee size of 450+, we have a strong PAN India and USA presence. With a thriving community of 300,000+ learners, ExcelR delivers impactful learning experiences across the globe. We proudly collaborate with premier institutes like IIT Madras, IIT Jammu, IIT Roorkee, and BITS Pilani, offering cutting-edge programs. Job Title: Data science Trainer Job Description: We are looking for a seasoned professional with in-depth expertise as a Data scientist. The ideal candidate should have a proven track record of hands-on experience with related field technologies, including managing complex projects, mentoring teams, and driving operational excellence in the field. Strong grasp of Python/R, Machine Learning, and statistical modeling Experience with data preprocessing, EDA, and model building Familiarity with libraries like NumPy, pandas, scikit-learn, and TensorFlow Proficiency in deploying models and working with real-world datasets Key Responsibilities: Develop, deliver, and continuously enhance training content and educational programs. Mentor and train junior in-house trainers, ensuring high-quality instruction across teams. Supervise the planning, execution, and evaluation of internships, assignments, and training programs. Innovate and maintain cutting-edge educational materials and content. Ideal Candidate Profile Demonstrated expertise in the relevant domain with industry experience Excellent communication and presentation abilities to deliver impactful training Passion for teaching and mentoring aspiring professionals Qualifications Prior experience in training, mentoring, or educational roles Strong interpersonal and time management skills Ability to collaborate effectively in a team environment Certifications in relevant subject areas or instructional design If youre an innovative, highly skilled professional with a passion for both technology and education, wed love to hear from you! Conditions:  Batch Management: Handle 3 batches consecutively, with assignments based on business requirements. This could include weekday/weekend and classroom batches.  Demos & Webinars: Conducting demo sessions and webinars.  Doubts Clarification Sessions: Organizing sessions to address and clarify students' doubts.  Course Material Preparation: Develop various teaching materials including presentations, assignments, projects, quizzes, and other relevant content.  Project Mentoring: Offer guidance and mentor-ship for student projects.  Placement Preparation: Assist students in preparing for placements, including conducting mock interviews.  Customer Query Handling: Addressing queries from potential customers.  Additional Responsibilities: Need to undertake other tasks as per the business requirement.

About Taggd: Taggd is a digital recruitment platform that provides Ready-to-Hire talent to India Inc. Combining the power of human knowledge and data, Taggd has successfully fulfilled talent mandates of more than 100+ clients and ensured hiring managers success for half a million jobs from over 14+ sectors. With a vision to fill 1 million Jobs through our talent platform by 2030, we strive to connect people with people, people with companies, and people with opportunities. Just right. Every time. For more information pls visit www.taggd.in About the Position: Designation: Machine Learning Engineer Domain Expertise: AI/ML Job Location: Gurgaon Working Days: 5 days (Hybrid) About the Role: At Taggd, our people are our most important resource. Were looking for a highly skilled recruiter to become one of them, and to help us find them. The ideal candidate will have prior experience in recruitment or talent acquisition, with knowledge of screening, interviewing, and hiring practices. If you have a passion for finding untapped talent, driving company growth, and helping individuals find promising careers, we want to hear from you. Job Requirements: Education: Btech Experience: 2-5 years Desired Competencies: Must have skills: Machine Learning, Python, LLM, Prompting Good to have: Predictive/ Statistical Modeling, Recommender System, Text Mining / Optimisation, Elasticsearch Must have solid hands-on experience python with data analysis and representation of the same. At least 3 years of relevant experience with Statistical Modelling, Predictive Analytics or Recommender Systems At least 1 year of relevant experience with LLM and prompting Decent Understanding of Machine Learning Algorithms and Neural Networks Prior experience with NLP and Elasticsearch is advantageous Expert in Logistic Regression based as well as other classification-based model building, segmentation techniques, clustering Desired Good knowledge of big data platforms and tools

Hi Team, Please find below our active remote requirement. Kindly share suitable CVs on a priority basis. Position: Machine Learning Engineer Experience: 3 Years Location: Remote Budget: Up to 8LPA Job Description: Bachelors/Masters/Ph.D. in Computer Science, Machine Learning, AI, Data Science, or related fields. 3+ years of relevant experience in AI/ML roles (MLE, MLR, or hybrid). Strong coding skills in Python and hands-on experience with ML engineering, research pipelines, and NLP. Familiarity with cloud environments (AWS, GCP) and containerized deployments (Docker, Kubernetes). Publications, patents, or contributions to open-source AI projects are an added advantage

As an accomplished Project Lead Python & AI Developer, your role involves leading end-to-end delivery of AI-powered analytics and product development initiatives. You will be responsible for overseeing multiple high-impact projects, managing cross-functional teams, and ensuring timely delivery under tight deadlines and high-pressure conditions. Key Responsibilities: - Lead, plan, and deliver multiple AI and analytics product development projects simultaneously with full ownership. - Translate complex business requirements into scalable, intelligent, and production-ready solutions. - Manage end-to-end project lifecycle, ensuring adherence to delivery timelines and quality benchmarks. - Guide, mentor, and review work of Python developers, AI engineers, and data analysts. - Set and enforce coding standards, architectural best practices, and delivery protocols. - Thrive in a high-pressure environment, balancing priorities across concurrent projects and stakeholders. In your role, you will be involved in: - Architecting, designing, and implementing AI-driven Python applications and intelligent automation frameworks. - Building and optimizing ETL pipelines, real-time data workflows, and analytics utilities. - Designing predictive modeling systems to forecast market trends and operational performance. - Leading the development of Genetic AI models for automated reporting, pattern detection, and process optimization. - Integrating APIs, databases, and cloud-based AI solutions (AWS, Azure, GCP) into scalable architectures. - Utilizing libraries such as Pandas, NumPy, SQL, Flask/FastAPI, TensorFlow, PyTorch, and scikit-learn to deliver high-quality analytical outputs. Furthermore, you will: - Design and deploy AI/ML models for predictive insights, anomaly detection, and strategic decision-making. - Drive the adoption of Genetic AI modeling techniques to improve forecasting accuracy and reporting intelligence. - Collaborate with cross-functional teams to integrate AI outcomes with business intelligence tools and automated dashboards. Your qualifications should include: - 10+ years of experience in Python development and AI engineering, preferably within product-oriented analytics environments. - Proven track record of leading multiple concurrent projects with successful delivery under tight timelines. - Strong hands-on experience in architecting predictive and AI modeling systems. - Expertise in Pandas, NumPy, SQL, Flask/FastAPI, REST APIs, and workflow automation. - Experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn). - Strong understanding of Genetic AI modeling, predictive analytics, and automated reporting pipelines. - Cloud experience on AWS, Azure, or GCP (any one mandatory). - Excellent debugging, optimization, and architectural design skills under demanding conditions. Good-to-Have Skills: - Experience with deep learning models, MLOps, and AI model lifecycle management. - Proficiency in Tableau, Power BI, or other BI and visualization tools. - Familiarity with DevOps (CI/CD, Docker, Jenkins, Git). - Experience in Agile/Scrum product development environments. Qualifications: - Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or an equivalent discipline.,

In this internship, you are expected to be a good coder who can solve coding problems efficiently. You may be assigned to work on simple and easy programs, but the key aspect is to ensure that you can explain your code clearly for learners and developers worldwide to comprehend. This opportunity will not only enhance your coding skills but also provide valuable research experience. As a Beginner or Intermediate Programmer, you will have the chance to learn and grow through assignments and projects of varying difficulty levels, enabling you to explore your potential and evolve into a better programmer. You will have the flexibility of working from home, which can be a significant advantage for you. There are no strict working hours; as long as you complete the assigned projects on time, you can manage your schedule efficiently and earn your compensation. **Minimum qualifications:** - Degree in Computer Science or related technical field, or equivalent practical experience. - Proficiency in coding using languages like C, C++, Java, JavaScript, or Python. **Preferred qualifications:** - Experience in Algorithms, Artificial Intelligence, Database, Data Mining, Distributed Systems, Machine Learning, Networking, or Systems. - Proficiency in Object Oriented Programming. - Strong foundation in computer science with expertise in data structures, algorithms, and software design. - Coding skills in Python or JavaScript/AJAX, database design and SQL, and/or knowledge of TCP/IP and network programming. - Ability to work independently. **Role and Responsibilities:** - Design and implement machine learning, information extraction, probabilistic matching algorithms, and models. - Utilize programming skills and deep learning/AI expertise using Python, TensorFlow, and frameworks like Keras, PyTorch to solve real-world problems. - Develop AI solutions in the computer vision field using convolutional neural networks (CNN) and a combination of deep neural networks such as CNN & RNN. - Solve object detection, recognition, image classification problems with machine learning and deep learning algorithms & transfer learning methods. - Implement innovative & automated approaches for data annotation, labeling, data augmentation, and active learning. - Provide online code assistance, code mentoring, and education-based solutions. Only candidates who: - are available for a full-time (in-office) internship - can commence the internship from 15th Jun'20 - are willing to commit to a duration of 6 months - possess relevant skills and interests **Perks:** - Certificate, Letter of recommendation - Flexible work hours - Informal dress code - 5 days a week - Free snacks & beverages,

You will be responsible for building deep learning models using TensorFlow/PyTorch and collaborating with the team to ensure proper testing and deployment. Your role will require a good understanding of Deep Learning Algorithms in both NLP (LSTMs, RNNs, etc.) and Computer Vision (CNNs, etc.) domains using TensorFlow, Keras, and PyTorch to solve real-life problems. You will also be involved in creating and updating documentation for your work and implementing deep learning algorithms such as LSTM, RNNs, DNNs, and BI-LSTMs from scratch. Additionally, you will work on Computer Vision and Image processing tasks, including TRANSFER LEARNING - GANs. Key Responsibilities: - Research machine learning/data science topics for writing articles for company websites - Assist with hands-on coding on Jupyter Notebook for providing code snippets in articles - Work on short projects & assignments, deployment techniques, and design and implement machine learning algorithms - Develop AI solutions in the computer vision domain using CNN and a combination of deep neural networks - Solve object detection, recognition, image classification problems using machine learning and deep learning algorithms, transfer learning methods, and techniques - Use innovative & automated approaches for data annotation, labeling, data augmentation, and active learning - Provide online code assistance, code mentoring, and education-based solutions Qualifications Required: - Master or PhD degree in Statistics, Applied Mathematics, or similar quantitative discipline, or equivalent practical experience - Relevant internship or work experience with data analysis - Experience with statistical software (R, Python, S-Plus, SAS, or similar) and database languages (e.g. SQL) Preferred qualifications: - Master or B.tech in relevant fields Please note that the company offers perks such as Certificate, Letter of recommendation, Flexible work hours, Informal dress code, 5 days a week, and Free snacks & beverages.,

Role Overview: As an AI Engineer specializing in Deep Learning and Medical Imaging, your role will involve envisioning, designing, developing, and deploying cutting-edge technologies to address real-world challenges in medical imaging. This includes tasks such as classification, semantic segmentation, object detection, landmark detection, image translation, and generation. You will also be responsible for analyzing datasets to identify patterns and trends that can enhance the learning, generalizability, and robustness of AI models. Additionally, formulating a data preparation and engineering strategy for research and development purposes will be a key aspect of your responsibilities. Key Responsibilities: - Engage in deep learning and image processing projects, with a focus on medical image processing. - Demonstrate proficiency and practical experience in general machine learning and AI concepts, including convolutional neural networks, optimization, hyperparameter tuning, model search, and model analysis. - Utilize machine learning libraries and frameworks such as PyTorch (Preferred), TensorFlow, and Keras, along with associated libraries like OpenCV, Pandas, PIL, and Matplotlib. - Collaborate with diverse cross-functional teams to analyze and extract insights for various AI/ML use cases. - Apply expertise in cloud technologies for tasks such as data preprocessing, feature engineering, and model training. - Design and optimize scalable machine learning pipelines to deploy models in production environments. - Stay informed about the latest advancements in machine learning to incorporate cutting-edge techniques into projects. - Mentor and guide junior team members, fostering a collaborative and knowledge-sharing environment. - Take ownership of end-to-end machine learning projects, from defining problems to deploying models. - Ensure reproducibility and version control of machine learning experiments. Qualifications Required: - 0-5 years of relevant work experience. - Experience in deep learning and image processing projects, particularly in the medical imaging domain. - Proficiency in general machine learning and AI concepts, along with practical experience in related technologies and frameworks. - Strong collaboration skills to work effectively with external stakeholders and internal teams. - Knowledge of cloud technologies for data processing and model deployment. - Strong problem-solving skills and a proactive approach to staying updated on industry advancements.,

As an AI/ML Workshop Instructor for the 5-day Intensive Program organized by MindLit Academy at Delhi Technological University (DTU) in the 2nd Week of January 2026, your role will involve leading practical and hands-on sessions to educate college students on Python fundamentals, AI/ML basics, data preprocessing techniques, core machine learning models, the California Housing Project, as well as introductory concepts of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI. The workshop will culminate with students constructing a complete resume-parsing ATS module. It is crucial for you to have a strong industry background, the ability to simplify complex topics, and a passion for teaching as these factors will significantly impact the success of the workshop and student motivation. In this role, success will be defined by students grasping core concepts, completing the final resume-parsing ATS project, engaging in interactive sessions suited for beginners, incorporating real-world examples into the learning experience, gaining confidence to pursue AI/ML further, and providing positive feedback on teaching quality and session clarity. Your responsibilities will include delivering structured lessons on Python, AI basics, and machine learning fundamentals, teaching data preprocessing techniques, guiding students through ML model development and deployment, introducing foundational concepts of LLMs, RAG systems, and Agentic AI, leading the final hands-on project, mentoring students of varying skill levels, preparing teaching materials, evaluating student progress, and coordinating with the organizing team for the smooth execution of the workshop. To qualify for this position, you should have a minimum of 3+ years of industry experience in AI/ML or related fields, strong proficiency in Python, machine learning algorithms, and data preprocessing, experience with LLMs, RAG workflows, or Agentic AI systems (preferred), ability to explain technical topics clearly to beginners, prior teaching or mentoring experience, excellent communication skills, and a degree in CS, Data Science, AI/ML, Engineering, or related fields (preferred). Your expertise as an AI/ML Workshop Instructor is crucial for delivering high-quality, industry-relevant education and bridging academic learning with real-world applications to provide students with a meaningful and career-oriented learning experience.,

As a Machine Learning / LLM Orchestrator, you will play a crucial role in architecting AI frameworks to empower every team member to independently build and deploy AI-driven features. Your responsibilities will include designing, fine-tuning, and deploying large language models (LLMs), developing adaptive machine learning models for transaction monitoring and fraud risk management, creating internal AI toolkits and frameworks, establishing best practices, and collaborating with leadership to shape the AI strategy and roadmap. - Build and fine-tune local LLM engines - Design automated pipelines for code generation, testing, documentation, and deployment - Develop adaptive machine learning models for transaction monitoring and fraud risk management - Create internal AI toolkits and frameworks for non-engineers to develop UI/UX, backend services, and ML workflows - Establish best practices for prompt engineering, model evaluation, and agent orchestration - Mentor engineers and product teams - Collaborate with leadership to shape the AI strategy and roadmap Qualifications: - At least 2 years of experience in building, fine-tuning, or deploying LLMs or custom ML models - Proficiency with PyTorch or TensorFlow - Familiarity with orchestration frameworks such as LangChain or LlamaIndex - Experience with CI/CD pipelines, Docker/Kubernetes, and microservices - Demonstrated ability to deliver production-ready AI solutions quickly and iteratively - Strong communication skills and a passion for empowering others through technology Join us to shape the future of AI-native fintech, with high autonomy and ownership to define AI frameworks and standards. Experience a fast-paced, experimentation-first environment that values innovation and learning. We offer competitive compensation and flexible remote/hybrid working options. (Note: Omitted the sections "About Company" and "How Are We Different" as they did not contain relevant information for the job description),

As an AI Engineer at our company, you will play a crucial role in designing, developing, and deploying intelligent systems using advanced AI and machine learning techniques. Your expertise will contribute directly to building efficient, scalable solutions that address real-world challenges and align with our organizational objectives. Key Responsibilities: - Design and develop custom AI models and machine learning algorithms. - Implement AI-driven features into existing systems to enhance user experience and business processes. - Manage data pipelines and infrastructure for AI development and deployment. - Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders. - Monitor and continuously improve the performance of deployed AI models. - Stay abreast of the latest advancements in artificial intelligence and propose innovations to enhance existing workflows and systems. Qualifications Required: - Bachelor's degree in Computer Science, Engineering, or a related technical field. - Proven experience in developing and deploying machine learning, deep learning, NLP, or computer vision solutions. - Proficiency in programming languages such as Python, Java, or R. - Hands-on experience with AI/ML frameworks and libraries like TensorFlow, PyTorch, Scikit-learn, etc. - Strong analytical and problem-solving skills. - Ability to work collaboratively in a fast-paced, team-oriented environment. This job also requires nice-to-have skills such as experience with cloud platforms (AWS, GCP, or Azure) for model deployment, familiarity with MLOps practices and tools (Docker, Kubernetes, CI/CD), and prior experience in deploying real-time or edge AI applications. Please note that the job description is referenced from hirist.tech.,

As a Research Scientist - Core AI Lead, your role will involve inventing new methods in deep learning and foundation models. You will be responsible for owning the research cycle from literature review to hypothesis formulation, method design, conducting experiments, writing papers, creating open-source artifacts, and transferring knowledge to product teams. Additionally, you will build rigorous evaluation processes including benchmarks, baselines, statistical tests, and ensuring reproducibility. Collaboration with engineers to scale training and inference by implementing distributed training, profiling, and improving efficiency will also be a key aspect of your role. Key Responsibilities: - Invent new methods in deep learning and foundation models - Own the research cycle end-to-end - Build rigorous evaluation processes - Collaborate with engineers to scale training and inference Qualifications Required: - PhD (preferred) or MS (Research) in AI/ML/CS - First-author, peer-reviewed papers proposing new models/algorithms/objectives in top venues within the last 3-4 years - Demonstrated experience in developing solutions for tabular/structured problems - Strong understanding of math and systems including linear algebra, probability, optimization, and experience with PyTorch or JAX - Exposure to agentic AI systems and experience in research related to single or multi-agent systems Additional Details: The company is not looking for candidates with computer-vision-heavy profiles or roles limited to prompting/RAG/agent wiring without novel methods or first-author papers. They are also not considering candidates with only application/survey papers without code or ablations to reproduce claims. If you meet the requirements and are interested in this position, you can share your resume to sandhia@hiresquad.in.,

As an AI Learning Specialist at Adobe, your role involves designing, implementing, and managing AI-powered learning solutions to drive adaptive, data-driven, and personalized learning experiences in corporate or educational environments. Your responsibilities will include: - Design & Development: - Creating adaptive learning modules using AI-powered platforms. - Collaborating with AI tools to co-develop learning content, videos, assessments, and microlearning. - Translating business needs into AI-based learning use cases for measurable impact. - Integration of AI Tools: - Collaborating with L&D teams and IT to integrate AI/ML tools into LMS/LXP environments. - Training internal stakeholders on utilizing AI tools for content generation, personalized learning, and data analysis. - Setting up chatbots and virtual assistants for on-demand learning support. - Learning Analytics & Optimization: - Leveraging AI and machine learning to analyze learner behavior, engagement, and knowledge gaps. - Providing actionable insights and recommendations for enhancing learning journeys using AI dashboards. - Continuously testing and iterating based on AI-driven insights and feedback. - Research & Innovation: - Staying updated on AI trends in education and L&D. - Evaluating new tools and proposing pilots or prototypes aligned with learning innovation goals. Qualifications: - Bachelors or Masters degree in Instructional Design, Education Technology, Computer Science, or related field. - 3-5 years of experience in L&D, instructional design, or digital learning development, with experience in managing sales and customer experience business. - Hands-on experience using AI tools in training, coaching, or content creation. - Strong understanding of adult learning principles and data-driven learning design. Preferred Traits: - Passion for learning innovation and emerging technologies. - Ability to translate technical concepts into engaging learning experiences. - Collaborative mindset with cross-functional teams (L&D, IT, HR, Product). Please note that Adobe is committed to creating exceptional employee experiences where everyone is respected and has equal opportunities. Adobe aims to make Adobe.com accessible to all users, and if you require accommodations, you can email accommodations@adobe.com or call (408) 536-3015.,

Veripoint Technologies is currently seeking skilled professionals in various roles including: - Machine Learning Engineers and Professionals - Product Marketing Professionals - Social Platforms Professionals - Coordinator and Client Success Manager If you are a talented individual with expertise in machine learning, product marketing, social platforms, or client success management, we invite you to apply and become a part of our dynamic team at Veripoint Technologies.,

You are a motivated PhD candidate interested in machine learning for histopathology image analysis. You will contribute to developing and optimizing deep learning models to analyze digitized H&E slides for cancer classification and spatial mapping. This role is well-suited for researchers aiming to apply advanced computational methods to biomedical challenges. Responsibilities: - Design, develop, and train convolutional neural networks (CNNs) and related ML models on H&E-stained histology images. - Use and extend tools such as QuPath for cell annotations, segmentation models, and dataset curation. - Preprocess, annotate, and manage large image datasets to support model training and validation. - Collaborate with cross-disciplinary teams to integrate image-based predictions with molecular and clinical data. - Analyze model performance and contribute to improving accuracy, efficiency, and robustness. - Document research findings and contribute to publications in peer-reviewed journals. Qualifications: - PhD in Computer Science, Biomedical Engineering, Data Science, Computational Biology, or a related discipline. - Demonstrated research experience in machine learning, deep learning, or biomedical image analysis (e.g., publications, thesis projects, or conference presentations). - Strong programming skills in Python and experience with ML frameworks such as TensorFlow or PyTorch. - Familiarity with digital pathology workflows, image preprocessing/augmentation, and annotation tools. - Ability to work collaboratively in a multidisciplinary research environment. Preferred: - Background in cancer histopathology or biomedical image analysis. - Knowledge of multimodal data integration, including spatial transcriptomics.,

As a Senior Software Engineer specializing in Machine Learning (ML) at Clarivate's Patent Service team in Noida, your primary focus will be on supporting ML projects. You will be responsible for deploying, scaling, and maintaining ML models in production environments. Collaborating closely with data scientists, ML engineers, and software developers, you will architect robust infrastructure, implement automation pipelines, and ensure the reliability and scalability of our ML systems. Key Responsibilities: - Designing and developing machine learning systems - Implementing appropriate ML algorithms and analyzing their success probability - Running ML tests, experiments, and statistical analysis - Implementing monitoring and alerting systems for ML model performance tracking - Ensuring security best practices in ML system deployment - Optimizing infrastructure for performance, scalability, and cost efficiency - Developing and maintaining CI/CD pipelines for automated model training, testing, and deployment - Troubleshooting infrastructure, deployment, and performance issues of ML models - Staying updated with the latest ML technologies and evaluating their impact on workflows Qualifications Required: - Holding a Bachelor's in Engineering or a Master's degree with strong communication and reasoning abilities - Proven experience as a Machine Learning Engineer or similar position - Deep knowledge of math, probability, statistics, and algorithms - Outstanding analytical and problem-solving skills - Understanding of data structures, data modeling, and software architecture - Good understanding of ML concepts and frameworks like TensorFlow, Keras, PyTorch - Proficiency in Python and libraries such as scikit-learn and pandas - Expertise in engineering and visualizing big datasets - Experience managing ML workload in production - Experience with MLOps or LLMOps concepts,

You will be joining Biz-Tech Analytics as a Junior Machine Learning Engineer (Computer Vision) with 1-2 years of experience. At Biz-Tech Analytics, the focus is on building production-grade computer vision and AI-driven automation solutions that turn complex data into actionable insights through scalable AI infrastructure. **Responsibilities:** - Contribute to the design, development, and deployment of Computer Vision models that power AI automation solutions. - Develop and deploy Computer Vision models for applications like object detection, tracking, segmentation, and visual inspections. - Work on image and video data pipelines including data preprocessing, augmentation, and annotation workflows. - Assist in model training, evaluation, and optimization to ensure performance benchmarks for accuracy and speed are met. - Collaborate with senior engineers on model deployment to edge/cloud environments. - Participate in code reviews, internal discussions, and brainstorming sessions to learn best practices for production-grade AI systems. - Take ownership of smaller modules and tasks within larger AI solution projects for timely and quality delivery. **Qualifications:** - Bachelors or Masters degree in Computer Science, AI, Machine Learning, Data Science, or a related field from a top-tier institute. - 1-2 years of experience (internships or projects) working on Machine Learning or Computer Vision. - Strong programming skills in Python. - Hands-on exposure to PyTorch or TensorFlow, OpenCV, and relevant CV libraries through internships, academic projects, or competitions. - Solid understanding of Computer Vision fundamentals: object detection, image segmentation, tracking, and image processing. - Familiarity with data preprocessing, augmentation, and basic model evaluation techniques. - A problem-solving mindset with a strong willingness to learn and take ownership of tasks. - Ability to work in a fast-paced, collaborative environment. - Good communication and documentation skills. **Good to have:** - Experience with vision-based automation in the manufacturing industry. - Exposure to Generative AI workflows. - Experience with Large Language Models (LLMs) and building multi-modal AI pipelines. - Understanding of AI governance, data compliance, and security protocols. At Biz-Tech Analytics, you will be working on challenging AI problems that demand innovation, leading end-to-end AI projects with full ownership, collaborating with a small, high-performing team where your contributions are visible and impactful, and experiencing a flexible, entrepreneurial work culture with opportunities for leadership and growth.,

As an experienced AI/ML Technical Architect with over 10 years of professional experience, you will be responsible for designing and scaling AI platforms and delivering enterprise-grade solutions. Your expertise in Machine Learning, Large Language Models (LLMs), LLMOps, and DevOps practices will be crucial in architecting and implementing innovative AI-driven solutions within a hybrid work environment. **Key Responsibilities:** - **AI Platform Development & Scalability** - Architect and build scalable AI platforms tailored to business and customer needs. - Ensure high availability, reliability, and performance of AI solutions. - Collaborate with stakeholders to evangelize platform adoption. - **Learning & Pipeline Design:** - Design and implement ML pipelines for experiment management, model training, deployment, and retraining. - Build and optimize APIs for model inferencing at scale. - Conduct A/B testing and ensure continuous improvement of models. - **LLM Expertise:** - Lead in the design, fine-tuning, and optimization of LLMs to improve accuracy and reduce latency. - Implement distributed training and serving of large language models. - Evaluate and recommend LLM models for specific business use. - **DevOps Practices:** - Implement LLMOps best practices using frameworks such as LangChain, LangGraph, LangFlow, and Flowise. - Manage deployments using Kubernetes, Docker, and container orchestration. - Monitor and optimize systems using tools like Prometheus, Grafana, Kibana. - **Data Systems:** - Design and manage AI solutions across major cloud platforms (AWS, Azure, GCP). - Work with a variety of databases and data warehouses such as DynamoDB, MongoDB, RDS, PostgreSQL, and BigQuery. - Ensure data integrity, scalability, and security in AI/ML solutions. - **Collaboration:** - Provide technical leadership and mentorship to engineering teams. - Partner with cross-functional stakeholders to align solutions with business goals. - Deliver end-to-end solutions from architecture design to production. **Skills & Qualifications:** - 10+ years of professional experience in AI/ML engineering and architecture. - Proven expertise in scaling AI platforms and designing ML pipelines & APIs. - Strong proficiency in LLMs, including fine-tuning, distributed training, and optimization. - Solid experience with LLMOps and DevOps tools & practices. - Proficient in Python, SQL, and JavaScript. - Hands-on experience with cloud platforms: AWS, Azure, GCP. - Strong understanding of modern data systems and microservices architectures. - Excellent leadership, problem-solving, and communication skills. **Certifications (Bonus):** - AWS Professional Solution Architect - AWS Machine Learning Specialty - Azure Solutions Architect Expert Please note that this job description is sourced from hirist.tech.,

Role Overview: As a Senior Machine Learning Engineer at TrueFan, you will play a crucial role in designing, developing, and deploying cutting-edge models for end-to-end content generation. Your focus will be on AI-driven image/video generation, lipsyncing, and multimodal AI systems using deep generative modeling techniques. You will contribute to creating highly realistic and controllable AI-generated media while staying updated with the latest trends in the field. Key Responsibilities: - Research & Develop: Design and implement state-of-the-art generative models such as Diffusion Models, 3D VAEs, and GANs for AI-powered media synthesis. - End-to-End Content Generation: Build and optimize AI pipelines for high-fidelity image/video generation and lipsyncing using diffusion and autoencoder models. - Speech & Video Synchronization: Develop advanced lipsyncing and multimodal generation models integrating speech, video, and facial animation. - Real-Time AI Systems: Implement and optimize models for real-time content generation and interactive AI applications using efficient model architectures. - Scaling & Production Deployment: Collaborate with software engineers to deploy models efficiently on cloud-based architectures (AWS, GCP, or Azure). - Collaboration & Research: Stay ahead of the latest trends in deep generative models and transformer-based vision systems to enhance AI-generated content quality. - Experimentation & Validation: Design and conduct experiments to evaluate model performance, improve fidelity, realism, and computational efficiency. - Code Quality & Best Practices: Participate in code reviews, improve model efficiency, and document research findings for team knowledge-sharing. Qualifications: - Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field. - 3+ years of experience working with deep generative models like Diffusion Models, 3D VAEs, GANs, and autoregressive models. - Strong proficiency in Python and deep learning frameworks such as PyTorch. - Expertise in multi-modal AI, text-to-image, image-to-video generation, and audio to lipsync. - Strong understanding of machine learning principles, statistical methods, and problem-solving abilities. - Good to have experience in real-time inference optimization, cloud deployment, and distributed training. - Familiarity with generative adversarial techniques, reinforcement learning for generative models, and large-scale AI model training. Preferred Qualifications: - Experience with transformers and vision-language models like CLIP, BLIP, GPT-4V. - Background in text-to-video generation, lipsync generation, and real-time synthetic media applications. - Experience in cloud-based AI pipelines (AWS, Google Cloud, or Azure) and model compression techniques. - Contributions to open-source projects or published research in AI-generated content, speech synthesis, or video synthesis. Role Overview: As a Senior Machine Learning Engineer at TrueFan, you will play a crucial role in designing, developing, and deploying cutting-edge models for end-to-end content generation. Your focus will be on AI-driven image/video generation, lipsyncing, and multimodal AI systems using deep generative modeling techniques. You will contribute to creating highly realistic and controllable AI-generated media while staying updated with the latest trends in the field. Key Responsibilities: - Research & Develop: Design and implement state-of-the-art generative models such as Diffusion Models, 3D VAEs, and GANs for AI-powered media synthesis. - End-to-End Content Generation: Build and optimize AI pipelines for high-fidelity image/video generation and lipsyncing using diffusion and autoencoder models. - Speech & Video Synchronization: Develop advanced lipsyncing and multimodal generation models integrating speech, video, and facial animation. - Real-Time AI Systems: Implement and optimize models for real-time content generation and interactive AI applications using efficient model architectures. - Scaling & Production Deployment: Collaborate with software engineers to deploy models efficiently on cloud-based architectures (AWS, GCP, or Azure). - Collaboration & Research: Stay ahead of the latest trends in deep generative models and transformer-based vision systems to enhance AI-generated content quality. - Experimentation & Validation: Design and conduct experiments to evaluate model performance, improve fidelity, realism, and computational efficiency. - Code Quality & Best Practices: Participate in code reviews, improve model efficiency, and document research findings for team knowledge-sharing. Qualifications: - Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field. - 3+ years of experience working with deep generative models like Diffusion Models, 3D VAEs, GANs, and autoregressive models. - Strong proficiency in Python and deep learning frameworks such as PyTorch. - Expertise in multi-modal AI, text-to-image,