34 integer Programming Jobs in Malegaon

Job Description: Paint QC Engineer / Executive Location: MalegaonDepartment: Quality / Paint ShopRole Type: Full-time Position Overview The Paint QC Engineer/Executive at Hyundai Motor India Limited is responsible for ensuring adherence to paint quality standards across all paint shop processesfrom pretreatment to topcoat application. The role involves process audits, defect analysis, documentation management, and driving continuous improvement to meet OEM and Tier-1 quality requirements. This position plays a crucial role in enhancing product quality, minimizing paint-related defects, and ensuring compliance with quality management systems. Key Responsibilities Quality Control & Inspection Monitor and ensure paint quality across all stages of painting, including pretreatment, ED coating, primer, basecoat, and topcoat. Conduct regular inspections and audits of painted bodies to identify defects and ensure adherence to standards. Perform quality confirmations for painted components as per Hyundai specifications. Defect Analysis & Improvement Analyze paint defects such as runs, sags, orange peel, dust, and pinholes to identify root causes. Implement corrective and preventive actions (CAPA) to minimize recurring defects. Support initiatives focused on continuous process improvement and defect reduction. Process Monitoring & Optimization Review paint process parameters and ensure compliance with Hyundai paint processes and approved operating procedures. Evaluate and improve inspection protocols, paint booths, ovens, and related equipment performance. Collaborate with production, maintenance, and supplier teams to optimize paint flow and quality. Documentation & Compliance Maintain documentation as per ISO and QMS requirements, including quality reports, audit findings, and SOPs. Ensure proper record-keeping for defect trends, inspections, and process deviations. Support internal and external audits conducted as part of the quality management system. Cross-functional Collaboration Coordinate with production, R&D, maintenance, and supplier teams to ensure consistent paint quality. Provide training and guidance to shop-floor employees on defect identification, paint quality standards, and inspection methodologies. Skills & Competencies Strong knowledge of paint quality, process improvement, and Hyundai paint process standards. Expertise in defect analysis, inspection protocols, and paint shop operations. Proficiency in root cause analysis tools (5 Why, Fishbone, Pareto). Good documentation and communication skills. Ability to work cross-functionally in a fast-paced manufacturing environment. Education & Experience B.E. in Mechanical / Automobile / Chemical Engineering or related field. 2-5 years of experience in Paint Shop Quality within automotive or Tier-1 manufacturing.

Job ID: ITC/P-E/20251030/23136 Role: Planning & Engagement Location: Malegaon Status: Open Role Overview The Planning & Engagement role at Hyundai Motor India Limited focuses on developing and executing employee engagement strategies to build a positive work culture, boost morale, and strengthen organizational values. The role involves coordinating engagement events, tracking engagement metrics, and supporting leadership communication initiatives. Key Responsibilities Design and implement employee engagement strategies. Plan and coordinate events, workshops, and activities to enhance team collaboration. Monitor engagement metrics through surveys, feedback, and data analysis. Support leadership communication and organization-wide messaging. Drive employee recognition programs and appreciation initiatives. Conduct awareness sessions to promote inclusivity and cultural alignment. Prepare presentations and engagement reports for leadership review. Required Skills Engagement strategy planning Event coordination Data analysis Strong communication skills Proficiency in MS PowerPoint (PPT skills) Qualification M.B.A Salary Range 6,00,000 15,00,000

Job ID: ITC/-S/20251030/24776 Role: L&D Specialist Location: Malegaon Status: Open   Role Overview The L&D Specialist will drive learning and development initiatives by identifying skill gaps, designing training programs, and enhancing employee capability across the organization. The role focuses on strategic training planning, soft skills development, and fostering a culture of continuous learning. Key Responsibilities Conduct Training Need Analysis (TNA) to identify skill and competency gaps. Align training programs with business goals and department requirements. Design, develop, and deliver targeted training programs. Manage and support industry certification programs. Conduct soft skills and behavioral training sessions. Evaluate training effectiveness using structured evaluation models. Handle training logistics, scheduling, and coordination. Promote continuous learning and employee development initiatives. Create professional training content and presentations (PPT skills). Required Skills Training Need Analysis Training Program Design & Delivery Soft Skills Training Strong Communication Skills PPT / Presentation Skills Qualification MBA (preferably in HR, L&D, or related fields) Experience Required 5 to 9 years in Learning & Development or training roles Salary Range 7,00,000 - 16,00,000

Hi, Greetings from MPS Management Services!!Open position leading in Life Insurance Company. Company Name- Star Union Daiichi (SUD) Life Insurance Profile - Branch Manager Channel- APC (Agency Partner Channel) Handling Partners Locations - Jalgaon, Aurangabad, Dhule, Nandurbar, Malegaon Ctc Budget -  upto 6.5 LPA Interested candidates can apply on the same,  RegardsPrincy YadavHR ExecutiveMPS Management Services

Job ID: ITC/TM/20251030/22304 Role: Time Management Location: Malegaon Status: Open   Role Overview This role focuses on end-to-end payroll and time management operations, ensuring accurate employee data administration and full statutory compliance. The candidate will be responsible for payroll accuracy, labor cost reporting, compensation processes, and supporting HR teams in total rewards and salary structures. Key Responsibilities Manage payroll processing and time management systems. Maintain and update employee personal data and records. Ensure statutory compliance for PF, Gratuity, Superannuation, NPS, etc. Prepare monthly MIS and labor cost reports. Support the design and maintenance of salary structures. Administer the annual compensation review cycle. Collaborate on total rewards programs and communication. Provide compensation guidance to HRBPs, recruiters, and managers. Ensure hands-on management of employee time and attendance systems. Required Skills Payroll Processing Time & Attendance Management Employee Data Administration Statutory Compliance Excel / MIS Reporting Qualification MPM (Master in Personnel Management) or equivalent HR specialization Experience Required 5 to 9 years (relevant HR/payroll experience preferred) Salary Range 5,00,000 - 10,00,000

Role Overview: As a Data Scientist specializing in operations research and analytics, your main responsibility will be to collaborate with cross-functional teams to define business problems and translate them into quantitative models such as optimization, simulation, and forecasting. You will be expected to extract, clean, and analyze large datasets to identify key drivers, bottlenecks, and opportunities for process improvement. Developing mathematical/OR models like linear programming, integer programming, and simulation to support decision-making will be a crucial part of your role. Additionally, you will implement and validate model prototypes, conduct what-if or sensitivity analyses, and present actionable recommendations to stakeholders. Monitoring model performance, tracking outcomes, and refining models iteratively will also be part of your responsibilities. Communication of complex analytical results in clear, non-technical language and creating dashboards or visualizations to track key metrics and business impact will be essential tasks. Key Responsibilities: - Collaborate with cross-functional teams to define business problems and translate them into quantitative models (e.g., optimization, simulation, forecasting). - Extract, clean, and analyze large datasets; identify key drivers, bottlenecks, and opportunities for process improvement. - Develop mathematical/OR models (e.g., linear programming, integer programming, simulation) to support decision-making (resource allocation, scheduling, supply-chain, manufacturing). - Implement and validate model prototypes; run what-if or sensitivity analyses and present actionable recommendations to stakeholders. - Monitor model performance, track outcomes, and iteratively refine models; document assumptions, methods, and results for business users. - Communicate complex analytical results in clear, non-technical language; create dashboards or visualizations to track key metrics and business impact. Qualifications Required: - Master's or Bachelor's in Operations Research, Industrial Engineering, Applied Math, Statistics, Computer Science, or related field. - 2-4 years of experience in analytics, operations research, or optimization. - Solid programming/statistical skills in Python, R, MATLAB, or similar. - Experience with optimization solvers/tools (e.g., CPLEX, Gurobi, or open-source equivalents) and simulation packages. - Strong SQL/database skills; experience working with large datasets and extracting insights. - Good understanding of operations research techniques (e.g., linear/integer programming, simulation, queues, network flows). - Ability to translate business questions into modeling frameworks and present results credibly to business and technical stakeholders. - Comfortable working in a dynamic environment, collaborating across teams, and managing ambiguity. - Experience in manufacturing/operations/supply-chain domain is a plus. - Prior exposure to dashboarding tools (e.g., PowerBI, Tableau) will be beneficial. - Some exposure to end-to-end solution deployment (data through to insights) would be valued. (Note: The job description does not include any additional details about the company.),

Role Overview: As an Operations Research Engineer, your primary responsibility will be to design and implement advanced optimization models including linear, integer, and nonlinear models. You will apply simulation, heuristics, and metaheuristics to solve complex business problems. Additionally, you will be developing high-performance algorithms using C programming and working with optimization solvers such as CPLEX, Gurobi, or COIN-OR. Your role will involve translating business challenges into mathematical models in collaboration with cross-functional teams and analyzing, benchmarking, and improving algorithm performance and solution quality. Key Responsibilities: - Design and implement advanced optimization models including linear, integer, and nonlinear. - Apply simulation, heuristics, and metaheuristics to solve complex business problems. - Develop high-performance algorithms using C programming. - Work with optimization solvers like CPLEX, Gurobi, or COIN-OR. - Translate business challenges into mathematical models in collaboration with cross-functional teams. - Analyze, benchmark, and improve algorithm performance and solution quality. Qualification Required: - Bachelors/Masters in Operations Research, Applied Mathematics, Computer Science, or related field. - Strong proficiency in C programming and optimization techniques (mandatory). - Deep understanding of mathematical modeling, algorithm design, and Operations Research methods. - Hands-on experience with solvers: CPLEX, Gurobi, or COIN-OR. - Knowledge of Python, C++, or Java is a plus.,

Role Overview: As a Demand Planning Specialist with expertise in SAS Viya and a foundation in AI/ML-driven forecasting, your primary responsibility will be to generate accurate product and location-level forecasts using advanced statistical models, AI, and machine learning. These insights will play a crucial role in driving smarter decisions related to inventory, supply chain, and pricing strategies. Key Responsibilities: - Develop and maintain short and long-term demand forecasts using SAS Viya for Demand Planning. - Apply advanced statistical models and AI/ML techniques to enhance forecast accuracy and responsiveness. - Collaborate with cross-functional teams including supply chain, sales, pricing, and others to ensure alignment of demand plans with overall business objectives. - Clean, prepare, and analyze large datasets for forecasting and performance monitoring. - Build interactive dashboards and reports using SAS Visual Analytics and other relevant tools. - Provide support for scenario planning, sensitivity analysis, and process automation initiatives. - Continuously monitor and enhance forecast performance through KPIs and regular analytics reviews. Qualification Required: - 45 years of experience in demand planning, forecasting, or supply chain analytics. - Hands-on expertise with SAS Viya and SAS Intelligent Planning. - In-depth knowledge of statistical forecasting methods such as ARIMA, exponential smoothing, etc. - Proficiency in SAS programming, data preparation, and SAS Visual Analytics. - Familiarity with AI/ML techniques and tools for demand forecasting. - Strong analytical, communication, and problem-solving skills. - Working knowledge of Python or R for advanced analytics. - Prior experience working in cloud-based SAS environments.,

Role Overview: You are a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with expertise in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. Your main role will involve playing a key part in the development and implementation of AI solutions, utilizing your technical proficiency. You should possess a deep understanding of AI technologies and have experience in designing and executing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be beneficial for this role. Responsibilities: - Contribute to the design and implementation of state-of-the-art AI solutions. - Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. - Collaborate with stakeholders to identify business opportunities and define AI project goals. - Stay updated with the latest advancements in generative AI techniques, such as LLMs, and assess their potential applications in solving enterprise challenges. - Utilize generative AI techniques, such as LLMs, to create innovative solutions for enterprise industry use cases. - Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. - Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. - Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. - Implement similarity search algorithms and techniques for efficient and accurate retrieval of relevant information from generative AI outputs. - Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and customize generative AI solutions accordingly. - Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to boost performance and efficiency. - Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. - Ensure compliance with data privacy, security, and ethical considerations in AI applications. - Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. - Minimum 3-7 years of experience in Data Science and Machine Learning. - In-depth knowledge of machine learning, deep learning, and generative AI techniques. - Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. - Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. - Familiarity with computer vision techniques for image recognition, object detection, or image generation. - Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. - Expertise in data engineering, including data curation, cleaning, and preprocessing. - Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. - Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. - Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. - Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. - Understanding of data privacy, security, and ethical considerations in AI applications. - Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: - Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. - Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). - Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. - Implement CI/CD pipelines for streamlined model deployment and scaling processes. - Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. - Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. - Implement monitoring and logging tools to ensure AI model performance and reliability. - Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. - Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.,

As a Senior Associate in data analysis at PwC, you will play a crucial role in leveraging data to drive insights and support clients in making informed business decisions. Your responsibilities will include utilizing advanced analytics techniques to extract insights from large datasets, manipulating data, creating visualizations, and employing statistical modeling to solve complex business problems. Key Responsibilities: - Proven expertise in supply chain analytics including demand forecasting, inventory optimization, logistics, segmentation, and network design - Hands-on experience with optimization methods like linear programming, mixed integer programming, scheduling optimization, and using third-party optimization solvers such as Gurobi - Proficiency in forecasting techniques like Holt-Winters, ARIMA, ARIMAX, SARIMA, SARIMAX, FBProphet, NBeats, and machine learning techniques (supervised and unsupervised) - Strong command of statistical modeling, testing, and inference - Proficient in GCP tools like BigQuery, Vertex AI, Dataflow, and Looker - Building data pipelines and models for forecasting, optimization, and scenario planning - Strong skills in SQL and Python programming, with experience deploying models in the GCP environment - Knowledge of orchestration tools like Cloud Composer (Airflow) Nice to Have: - Familiarity with MLOps, containerization (Docker, Kubernetes), and orchestration tools like Cloud Composer - Strong communication and stakeholder engagement skills at the executive level Qualifications Required: - BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA from a reputed institute,

You will be a Data Scientist with 3-6 years of experience, specializing in classic machine learning models. Your role will involve GCP deployment, regression, classification, and casting mechanisms. You will be expected to have expertise in machine learning techniques such as classification, regression, computer vision, and neural networks. Additionally, your responsibilities will include utilizing algorithms like decision tree and boosting techniques. Your technical skills should encompass tools like TensorFlow, Keras, PyTorch, OpenCV, Seaborn, Numpy, Pandas, Selenium, SQL, Git/GitLab, Spark, JIRA, ScikitLearn, and optimization methods. - Apply scientific methods to analyze and solve software engineering problems - Develop and apply software engineering practices and knowledge in research, design, development, and maintenance - Exercise original thought and judgment while supervising the technical and administrative work of other software engineers - Build skills and expertise in software engineering discipline to meet standard expectations for the role - Collaborate effectively with other software engineers and stakeholders - 3-6 years of experience as a Data Scientist - Proficiency in classic machine learning models - Strong knowledge of GCP deployment, regression, classification, and casting mechanisms - Skills in business analysis, analytical thinking, problem-solving, decision-making, leadership, managerial, and time management - Expertise in machine learning techniques like classification, regression, computer vision, and neural networks - Familiarity with algorithms such as decision tree and boosting techniques - Technical proficiency in TensorFlow, Keras, PyTorch, OpenCV, Seaborn, Numpy, Pandas, Selenium, SQL, Git/GitLab, Spark, JIRA, and ScikitLearn - Experience with optimization methods including linear, quadratic, integer, convex, dynamic programming, quasi-Newton methods, and numerical methods - Database skills in MsSQL, Postgres, MsAccess, GCP, and Vertex AI The company works in the field of Software Engineering, focusing on the development, maintenance, and optimization of software solutions and applications. As a senior software engineer at Capgemini, you will lead the development of tools for Data Scientists and classic machine learning, cloud machine deployment, and casting mechanisms. You will also explore Python skills as part of your responsibilities, collaborating effectively with other team members and stakeholders.,

In this role as a Senior Business Analyst, Data Science at Kenvue, you will be responsible for delivering Optimization solutions to cross-functional Supply Chain teams. Your main tasks will involve working with subject matter experts to understand business context and key questions, collaborating with various teams to ensure the delivery of scalable data science solutions, and reporting findings clearly and structured manner. Key Responsibilities: - Develop, refine, and review mathematical models representing supply chain systems - Apply advanced optimization techniques like linear programming and heuristic algorithms to solve complex supply chain problems - Conduct sensitivity analysis and risk assessment to evaluate the impact of different factors on supply chain performance - Collaborate with stakeholders to translate business objectives into mathematical models and optimization problems - Analyze large datasets, extract relevant information, and identify patterns and trends - Gather and preprocess data from various sources to ensure accuracy and integrity - Generate actionable insights and recommendations based on data analysis to optimize supply chain operations - Present findings, insights, and recommendations clearly and concisely - Make solution recommendations balancing speed to market and analytical soundness - Collaborate with internal stakeholders to ensure timely testing and deployment of the product - Stay updated with the latest developments in operations research and supply chain management - Explore innovative approaches to address supply chain challenges and drive continuous improvement Qualifications: - Master's in Industrial Engineering, Operations Research, or Management Science - Proficiency in mathematical modeling, optimization techniques, and programming languages like Python, R, or MATLAB - Experience with data analysis, statistical modeling, and visualization tools like SQL, Tableau, or Power BI - Knowledge of supply chain concepts including demand forecasting, inventory management, and transportation logistics Additionally, Kenvue is a global company with a diverse team of passionate individuals committed to delivering the best products to customers. As a Kenvuer, you will have the opportunity to impact the lives of millions of people every day. Join us in shaping the future of the company and yours.,

As a Sales Executive at Toyota Showroom in Malegaon, your main responsibility will be to sell new cars to customers. Your work schedule will be full-time and permanent with day shifts. Fluency in English is preferred to effectively communicate with customers. Key Responsibilities: - Sell new cars to customers - Meet sales targets - Provide excellent customer service - Maintain knowledge of latest car models and features Qualifications Required: - Graduation in any field - At least 1 year of experience in selling cars Please note that health insurance and provident fund benefits are provided. The work location is in person at the Toyota Showroom in Malegaon. If interested, you can contact the employer at +91 9607999323.,

As a Staff Engineer at Enphase Energy, you will be a key player in leading the development of advanced simulation frameworks and products for Home Energy Management Systems (HEMS). Your expertise in simulation, optimization, and AI-driven forecasting will contribute to our mission of enabling intelligent, cost-effective, and sustainable energy use in residential homes. **Key Responsibilities:** - Architect and implement simulation frameworks that scale to millions of homes by modeling PV systems, battery storage, HVAC, heat pumps, water heaters, EVSE, and grid interactions. - Ensure scalability, modularity, and maintainability of simulation tools and their data pipeline. - Conduct what-if analyses to evaluate the impact of different configurations on a homeowner's bill. - Collaborate with product managers, data scientists, and software engineers to translate simulation insights into product features. - Contribute to technical strategy, mentor junior engineers, and lead cross-functional initiatives. - Document and record results effectively. **Key Qualifications:** - Bachelor's or master's degree in Electrical Engineering, Mechanical Engineering, Energy Systems, Computer Science, or a related field. - 7+ years of experience in energy systems modeling, simulation, or optimization. - Strong experience in modeling residential energy devices, hands-on modeling simulation tools for home energy management, formulating and solving Mixed Integer Linear Programming (MILP) problems. - Proficiency in Python and relevant libraries (e.g., Pyomo, Pandas, NumPy, Scikit-learn). - Experience with simulation tools such as Energy Plus or any other open-source tools. - Proven ability to design and deliver scalable, production-grade software. Join Enphase Energy's dynamic teams to design and develop next-gen energy technologies and contribute to driving a sustainable future!,

As a Senior Data Scientist at EY, you will be responsible for designing and implementing state-of-the-art Agentic AI solutions tailored for the financial and accounting industry. Your key responsibilities will include developing and implementing AI models and systems using techniques such as Language Models (LLMs) and generative AI to solve industry-specific challenges. You will collaborate with stakeholders to identify business opportunities, stay updated with the latest advancements in generative AI techniques, and integrate with relevant APIs and libraries to enhance generative AI capabilities. Your role will also involve implementing and optimizing end-to-end pipelines for generative AI projects, utilizing vector databases to handle large-scale datasets efficiently, and collaborating with domain experts to tailor generative AI solutions as per specific business requirements. Additionally, you will establish evaluation metrics to assess the quality and relevance of generative AI outputs and ensure compliance with data privacy, security, and ethical considerations in AI applications. Qualifications & Skills: - Education: Bachelors/Masters in Computer Science, Engineering, or related field (Ph.D. preferred). - Experience: 4+ years in Data Science/Machine Learning with proven end-to-end project delivery. - Technical Expertise: Strong in ML, deep learning, generative AI, RAG, and agentic AI design patterns. - Programming Skills: Proficient in Python (plus R), with hands-on experience in TensorFlow, PyTorch, and modern ML/data stacks. - GenAI Frameworks: Experience with LangChain, LangGraph, Crew, and other agentic AI frameworks. - Cloud & Infrastructure: Skilled in AWS/Azure/GCP, containerization (Docker, Kubernetes), automation (CI/CD), and data/ML pipelines. - Data Engineering: Expertise in data curation, preprocessing, feature engineering, and handling large-scale datasets. - AI Governance: Knowledge of responsible AI, including fairness, transparency, privacy, and security. - Collaboration & Communication: Strong cross-functional leadership with the ability to align technical work to business goals and communicate insights clearly. - Innovation & Thought Leadership: Track record of driving innovation, staying updated with the latest AI/LLM advancements, and advocating best practices. Good to Have Skills: - Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models. - Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). - Deep knowledge of classical AIML (regression, classification, time series, clustering). - Drive DevOps and MLOps practices, covering CI/CD and monitoring of AI models. - Implement CI/CD pipelines for streamlined model deployment and scaling processes. - Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. - Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. - Implement monitoring and logging tools to ensure AI model performance and reliability. - Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Join EY in building a better working world by creating new value for clients, people, society, and the planet, while building trust in capital markets. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy, and transactions, providing services in more than 150 countries and territories with the help of data, AI, and advanced technology.,

As a Logistics Operations Leader for a cluster of bioenergy plants, your role involves optimizing operations to ensure the efficient, cost-effective, and timely movement of feedstock and CNG/CBG across the supply chain. **Key Responsibilities:** - Managing inbound and outbound movements of feedstock and CNG/CBG - Working towards value maximization, cost optimization, and finalizing freight agreements - Overseeing transportation, warehousing, and inventory flow - Appointing vendors and defining freight requirements - Coordinating with procurement, production, and sales teams - Ensuring compliance with regulatory and safety standards - Developing and implementing logistics strategies - Managing vendor relationships and logistics contracts **Key Requirements:** - Bachelor's degree in Engineering, MBA, Supply Chain, or a related field - 7-20 years of experience in logistics, preferably in the energy/biofuels industry - Strong leadership, analytical, and communication skills *Location: Malegaon, Akola, Nanded Yavatmal, MH*,

Role Overview: As a Senior AI Engineer (Tech Lead) at EY, you will be a crucial part of the team, utilizing your expertise in Data Science and Machine Learning to design and implement cutting-edge AI solutions. With a minimum of 4 years of experience, preferably in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture, you will play a key role in the development and implementation of AI solutions. Your deep understanding of AI technologies will be instrumental in creating innovative AI models and systems. Additionally, your proficiency in data engineering, DevOps, and MLOps practices will be highly valued in this role. Responsibilities: - Contribute to the design and implementation of state-of-the-art AI solutions. - Lead a team of 4-6 developers. - Assist in the development and implementation of AI models and systems, utilizing techniques such as Large Language Models (LLMs) and generative AI. - Collaborate with stakeholders to identify business opportunities and define AI project goals. - Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. - Utilize generative AI techniques like LLMs, Agentic Framework to develop innovative solutions for enterprise industry use cases. - Integrate with relevant APIs and libraries such as Azure Open AI GPT models and Hugging Face Transformers to enhance generative AI capabilities. - Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. - Utilize vector databases like Redis and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. - Implement similarity search algorithms and techniques for efficient retrieval of relevant information from generative AI outputs. - Collaborate with domain experts, stakeholders, and clients to tailor generative AI solutions to specific business requirements. - Conduct research and evaluation of advanced AI techniques to enhance performance and efficiency. - Establish evaluation metrics and methodologies to assess the quality of generative AI outputs for enterprise industry use cases. - Ensure compliance with data privacy, security, and ethical considerations in AI applications. - Leverage data engineering skills for data curation, cleaning, and preprocessing for generative AI applications. Requirements: - Bachelor's or Master's degree in Computer Science, Engineering, or related field. - Minimum 4 years of experience in Python, Data Science, Machine Learning, OCR, and document intelligence. - Experience in leading a team of 4-6 developers. - In-depth knowledge of machine learning, deep learning, and generative AI techniques. - Proficiency in programming languages like Python, R, and frameworks such as TensorFlow or PyTorch. - Strong understanding of NLP techniques and frameworks like BERT, GPT, or Transformer models. - Familiarity with computer vision techniques for image recognition, object detection, or image generation. - Strong knowledge of Python frameworks such as Django, Flask, or FastAPI. - Experience with RESTful API design and development. - Experience with cloud platforms like Azure, AWS, or GCP and deploying AI solutions. - Expertise in data engineering, data curation, cleaning, and preprocessing. - Knowledge of trusted AI practices for fairness, transparency, and accountability in AI models. - Strong collaboration skills with software engineering and operations teams. - Excellent problem-solving and analytical skills to translate business requirements into technical solutions. - Strong communication and interpersonal skills for effective collaboration with stakeholders. - Understanding of data privacy, security, and ethical considerations in AI applications. - Track record of innovation and staying updated with the latest AI research. Good to Have Skills: - Understanding of agentic AI concepts and frameworks. - Proficiency in designing or interacting with agent-based AI architectures. - Apply trusted AI practices for fairness, transparency, and accountability. - Utilize optimization tools like MIP (Mixed Integer Programming). - Drive DevOps and MLOps practices for continuous integration, deployment, and monitoring of AI models. - Implement CI/CD pipelines for streamlined model deployment and scaling processes. - Utilize tools like Docker, Kubernetes, and Git for building and managing AI pipelines. - Apply infrastructure as code (IaC) principles with tools like Terraform or CloudFormation. - Implement monitoring and logging tools for AI model performance and reliability. - Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.,

As a Quality Engineer, you will be responsible for ensuring the quality of products by conducting inspections and testing throughout the manufacturing process. Your expertise in machining processes, documentation, and process improvement techniques will be crucial for this role. Key Responsibilities: - Conduct visual and physical inspections of raw materials, in-process parts, and finished products to ensure they meet specifications and quality standards. - Record all inspection findings, test results, and defect reports in a clear, organized manner. - Identify defective products or materials and initiate non-conformance reports. - Notify supervisors of quality issues and collaborate with production and engineering teams to resolve problems and implement corrective actions. - Monitor automated inspection systems and ensure quality control procedures are followed throughout the manufacturing process. - Maintain detailed records of inspections, audits, and corrective actions taken. Qualifications Required: - 13 years of experience in quality inspection. - Diploma in Mechanical Engineering (DME) or Bachelor of Engineering (BE). As a part of our team, you will play a key role in maintaining the quality standards of our products. This is a full-time, permanent position located in Malegaon, Sinnar, Nashik Maharashtra.,

As an experienced candidate with over 8 years of relevant experience, you will be responsible for the following key tasks: - Running complex queries against large datasets using advanced proficiency in SQL, preferably with Google BigQuery. - Utilizing strong Python programming skills, including extensive experience with the pandas library for data manipulation, analysis, and automation. - Applying operations research and modeling basics, such as linear programming and integer programming in practical scenarios. - Demonstrating expertise in Microsoft Excel, including pivot tables and advanced formulas for data analysis. - Developing a comprehensive understanding of supply chain operations, particularly within distribution centers. - Adapting to changing project priorities, managing a dynamic workload effectively, and being flexible in your approach. - Utilizing Tableau or similar data visualization software to present findings effectively. Additionally, if available, any additional details about the company will be included here.,

Role Overview: As a Senior Data Scientist at EY GDS Data and Analytics (D&A), you will leverage your expertise with a minimum of 3 - 7 years of experience in Data Science and Machine Learning to play a key role in developing and implementing AI solutions. Your deep understanding of AI technologies and experience in designing cutting-edge AI models will be crucial in this role. Additionally, proficiency in data engineering, DevOps, and MLOps practices will add value to your responsibilities. Responsibilities: - Contribute to the design and implementation of state-of-the-art AI solutions. - Assist in developing and implementing AI models and systems, utilizing techniques like Language Models (LLMs) and generative AI. - Collaborate with stakeholders to identify business opportunities and define AI project goals. - Stay updated with advancements in generative AI techniques, such as LLMs, and assess their potential applications in solving enterprise challenges. - Utilize generative AI techniques, like LLMs, to innovate solutions for enterprise industry use cases. - Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, for enhanced generative AI capabilities. - Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. - Utilize vector databases, like Redis, and NoSQL databases for efficient handling of large-scale generative AI datasets. - Implement similarity search algorithms for accurate retrieval of relevant information from generative AI outputs. - Collaborate with domain experts, stakeholders, and clients to tailor generative AI solutions to specific business requirements. - Research and evaluate advanced AI techniques to enhance performance and efficiency. - Establish evaluation metrics to assess the quality and relevance of generative AI outputs for enterprise industry use cases. - Ensure compliance with data privacy, security, and ethical considerations in AI applications. - Utilize data engineering skills for data curation, cleaning, and preprocessing for generative AI applications. Requirements: - Bachelor's or Master's degree in Computer Science, Engineering, or related field (Ph.D. is a plus). - 3-7 years of experience in Data Science and Machine Learning. - In-depth knowledge of machine learning, deep learning, and generative AI techniques. - Proficiency in Python, R, TensorFlow, or PyTorch. - Strong understanding of NLP techniques and frameworks like BERT, GPT, or Transformer models. - Experience with cloud platforms such as Azure, AWS, or GCP. - Expertise in data engineering, trusted AI practices, and collaboration with software engineering teams. - Excellent problem-solving skills and ability to translate business requirements into technical solutions. - Strong communication and interpersonal skills. - Understanding of data privacy, security, and ethical considerations in AI applications. - Track record of innovation and staying updated with AI research. Good to Have Skills: - Apply trusted AI practices for fairness, transparency, and accountability. - Utilize optimization tools like MIP. - Drive DevOps and MLOps practices for continuous integration and deployment. - Implement CI/CD pipelines for streamlined model deployment. - Use tools such as Docker, Kubernetes, and Git for managing AI pipelines. - Apply infrastructure as code principles with tools like Terraform or CloudFormation. - Implement monitoring and logging tools for AI model performance. - Collaborate effectively with software engineering and operations teams.,