12 Pyomo Jobs

We are seeking an Optimization Specialist focused on developing and deploying advanced analytical solutions leveraging mathematical optimization techniques. In this role, you will play a pivotal part in shaping the future of manufacturing operations by designing, developing, and deploying innovative scheduling solutions that optimize complex business processes The ideal candidate will excel in formulating and solving various optimization problems (LP, MILP, combinatorial optimization, scheduling, etc.) and will be adept in applying innovative algorithms to achieve optimal solutions. Our current technical environment: Language: Python Frameworks/Others: COIN-OR , PyTorch, NumPy, SciPy, Pyomo and Django Application Architecture: Scalable, Resilient, Reactive, event driven, secure microservices architecture. Cloud: AWS What you’ll do: Mathematical Optimization Solvers: Design, develop, and implement advanced mathematical optimization models and solvers to address complex business challenges across various domains, such as scheduling, routing, resource allocation, and inventory management. Identify and model optimization problems across different kinds of Manufacturing businesses, focusing on LP, MILP, combinatorial optimization, and scheduling. Design and implement robust optimization algorithms, including both classical methods and advanced heuristic and metaheuristic techniques Evaluate and select appropriate non-commercial (e.g., COIN-OR, SCIP) and commercial solvers (e.g., Gurobi, CPLEX, COIN-OR, PuLP or AMPL) for specific problems, customizing and extending as necessary. Machine Learning Model Development: Design, develop, and deploy machine learning models to analyze large datasets, generate insights, and make predictions that support data-driven decision-making, specifically related to enhancing the performance of optimization algorithms. Perform data analysis and statistical validation of models and solutions, ensuring accuracy and efficacy. Keep abreast of the latest developments in optimization and computational intelligence, incorporating these advancements into problem-solving strategies. Push the team towards better quality software by constructively pointing out opportunities to reduce complexity and to write cleaner code and more effective tests. Identify root causes of issues and fixes those rather than their symptoms. Design services to be self-healing and to offer self-service capabilities from the ground up to achieve minimum manual intervention. What we are looking for: 1-3 years of experience in Operations Research and Python programming Bachelors in Operations Research, Applied Mathematics, Statistics, Computer Science, Data Science, or a related field. Has experience building optimization models from scratch Preferably have some constraint programming knowledge and know-how to Understand standard scheduling / job shop model models and improve upon them Demonstrable experience with both non-commercial and commercial optimization solvers, with a keen ability to tailor solutions to complex problems. Strong statistical analysis skills, with proficiency in tools such as Python. Excellent problem-solving abilities, creativity in approach, and a track record of innovative solutions in optimization. Effective communication skills for presenting complex concepts to technical and non-technical audiences. About Techtinium Techtinium has a passion for innovative products. Specializing in the design and development of exceptional software, our diverse team includes developers, architects, designers, analysts, testers, project managers, and proud caffeine enthusiasts. Our success is rooted in the belief that our people are our greatest asset. Through careful selection, sourcing, hiring, and retention, we’ve cultivated a team of intelligent and motivated experts dedicated to delivering superior software solutions. At Techtinium, we consistently exceed expectations, fostering enduring relationships that have led to the establishment of separate dedicated companies to manage and nurture our products. Joining Techtinium means embarking on a journey where your skills are honed across the entire software development lifecycle. From mastering scalable applications to thriving in a positive, thought-provoking, and collaborative environment, your contributions will be valued in shaping creative solutions for our global clientele. If you’re ready for an exciting professional adventure, explore opportunities with us at https://techtinium.com/. We’re eager to welcome you to our team!

Key Responsibilities JOB DESCRIPTION Lead Inventory and Pricing Optimization Initiatives: Design and implement predictive and prescriptive models to optimize inventory placement, demand forecasting, pricing optimization, clearance models etc. Advanced Modeling & Machine Learning: Apply techniques such as time series forecasting, probabilistic modeling, optimization algorithms (e.g., MIP), and reinforcement learning to solve inventory and pricing-related problems. Cross-functional Collaboration: Partner with stakeholders across supply chain, merchandising, and technology to align machine learning/analytics initiatives with business goals and operational constraints. Innovation & Thought Leadership: Identify emerging trends and technologies in supply chain and pricing optimization; evaluate and prototype novel and pragmatic solutions to complex problems. Mentoring & Leadership: Provide technical mentorship to other data scientists and contribute to the overall impactful growth of the organization. Effective Communication: Have effective communication skills to convey complex quantitative analyses, analytic methodologies, and findings in a clear, concise, and actionable manner Operational Impact: Translate data insights into actionable recommendations that directly influence decisions around inventory planning, replenishment, and distribution. What We're Looking For PhD or Master’s degree in a quantitative field from a reputed college (e.g., Operations Research, Statistics, Computer Science) 10+ years of industry experience in data science, with a strong focus on inventory, pricing and supply chain optimization Deep understanding of inventory theory, supply chain planning, stochastic modeling, forecasting and optimization techniques Proficient in Python, SQL, and one or more optimization libraries (e.g., Gurobi, Pyomo) Strong background in ML model development and experience in implementing large models in production. Experience with large-scale data platforms (e.g., Spark, Snowflake, Databricks) Strong business acumen with the ability to communicate complex technical ideas to non-technical stakeholders Preferred Qualifications Experience in retail, e-commerce, or manufacturing supply chains Familiarity with WMS, and/or Network optimization tools (Optilogic, Llamasoft) Experience working in Agile or cross-functional product teams Prior experience leading technical teams or projects About Us Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally. About The Team Fanatics Commerce is a leading designer, manufacturer, and seller of licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods. It operates a vertically-integrated platform of digital and physical capabilities for leading sports leagues, teams, colleges, and associations globally – as well as its flagship site, www.fanatics.com. Fanatics Commerce has a broad range of online, sports venue, and vertical apparel partnerships worldwide, including comprehensive partnerships with leading leagues, teams, colleges, and sports organizations across the world—including the NFL, NBA, MLB, NHL, MLS, Formula 1, and Australian Football League (AFL); the Dallas Cowboys, Golden State Warriors, Paris Saint-Germain, Manchester United, Chelsea FC, and Tokyo Giants; the University of Notre Dame, University of Alabama, and University of Texas; the International Olympic Committee (IOC), England Rugby, and the Union of European Football Associations (UEFA). At Fanatics Commerce, we infuse our BOLD Leadership Principles in everything we do: Build Championship Teams Obsessed with Fans Limitless Entrepreneurial Spirit Determined and Relentless Mindset

Title : Principal Data scientist Location : Chennai or Bangalore Experience : 10-13 years Job Summary We are seeking a highly skilled and techno-functional Optimization Specialist with 1013 years of experience in developing enterprise-grade optimization solutions and platforms. The ideal candidate will possess deep expertise in mathematical optimization, strong hands-on Python programming skills, and the ability to bridge the gap between technical and business teams. You will lead the design and deployment of scalable optimization engines to solve complex business problems across supply chain, manufacturing, pricing, logistics, and workforce planning. Key Responsibilities Design & Development : Architect and implement optimization models (LP, MILP, CP, metaheuristics) using solvers like Gurobi, CPLEX, or open-source equivalents. Platform Building : Lead the design and development of optimization-as-a-service platforms with modular, reusable architecture. Techno-Functional Role : Translate business requirements into formal optimization problems and provide functional consulting support across domains. End-to-End Ownership : Manage the full lifecycle from problem formulation, model design, data pipeline integration, to production deployment. Python Expertise : Build robust, production-grade code with modular design using Python, Pandas, NumPy, Pyomo/Pulp, and APIs (FastAPI/Flask). Collaboration : Work with business stakeholders, data scientists, and software engineers to ensure solutions are accurate, scalable, and aligned with objectives. Performance Tuning : Continuously improve model runtime and performance; conduct sensitivity analysis and scenario modeling. Innovation : Stay abreast of the latest in optimization techniques, frameworks, and tools; proactively suggest Skills & Qualifications : Bachelors or Masters in Operations Research, Industrial Engineering, Computer Science, or related fields. 1012 years of experience in solving real-world optimization problems. Deep understanding of mathematical programming (LP/MILP/CP), heuristics/metaheuristics, and stochastic modeling. Proficiency in Python and experience with relevant libraries (Pyomo, Pulp, OR-Tools, SciPy). Strong experience building end-to-end platforms or optimization engines deployed in production. Functional understanding of at least one domain : supply chain, logistics, manufacturing, pricing, scheduling, or workforce planning. Excellent communication skills able to interact with technical and business teams effectively. Experience integrating optimization models into enterprise systems (APIs, cloud deployment, Qualifications : Exposure to cloud platforms (AWS, GCP, Azure) and MLOps pipelines. Familiarity with data visualization (Dash, Plotly, Streamlit) to present optimization results. Certification or training in operations research or mathematical optimization tools. (ref:hirist.tech)

We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities Lead and contribute to internal optimization-focused data science projects from design to deployment. Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. Collaborate with business stakeholders to gather requirements and translate them into data science use cases. Build robust data pipelines and use statistical and machine learning methods to drive insights. Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. Minimum 8 years of relevant experience in data science, with a strong focus on optimization. Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. Experience with end-to-end lifecycle of internal optimization projects. Strong analytical and problem-solving skills. Excellent communication and stakeholder management abilities. Preferred Qualifications Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. Familiarity with dashboards and visualization tools like Power BI or Tableau. Prior experience in consulting or internal centers of excellence (CoE) is a plus. Additional Notes This is a contractual/project-based role and not a permanent/full-time position. Compensation will be finalized post-interview, based on mutual agreement and project scope. The project may be divided into phases, with compensation linked to successful milestone completion. Skills: data science , communication , mentoring , optimization , metaheuristic algorithms,sql,linear programming,data pipelines,python,machine learning,mathematical optimization,mixed-integer programming,operations research,statistical methods,heuristic algorithms

Title : Principal Data scientist Location: Chennai or Bangalore Experience: 10-13 years Job Summary We are seeking a highly skilled and techno-functional Optimization Specialist with 10–13 years of experience in developing enterprise-grade optimization solutions and platforms. The ideal candidate will possess deep expertise in mathematical optimization, strong hands-on Python programming skills, and the ability to bridge the gap between technical and business teams. You will lead the design and deployment of scalable optimization engines to solve complex business problems across supply chain, manufacturing, pricing, logistics, and workforce planning. Key Responsibilities Design & Development : Architect and implement optimization models (LP, MILP, CP, metaheuristics) using solvers like Gurobi, CPLEX, or open-source equivalents. Platform Building : Lead the design and development of optimization-as-a-service platforms with modular, reusable architecture. Techno-Functional Role : Translate business requirements into formal optimization problems and provide functional consulting support across domains. End-to-End Ownership : Manage the full lifecycle from problem formulation, model design, data pipeline integration, to production deployment. Python Expertise : Build robust, production-grade code with modular design using Python, Pandas, NumPy, Pyomo/Pulp, and APIs (FastAPI/Flask). Collaboration : Work with business stakeholders, data scientists, and software engineers to ensure solutions are accurate, scalable, and aligned with objectives. Performance Tuning : Continuously improve model runtime and performance; conduct sensitivity analysis and scenario modeling. Innovation : Stay abreast of the latest in optimization techniques, frameworks, and tools; proactively suggest enhancements. Required Skills & Qualifications Bachelor’s or Master’s in Operations Research, Industrial Engineering, Computer Science, or related fields. 10–12 years of experience in solving real-world optimization problems. Deep understanding of mathematical programming (LP/MILP/CP), heuristics/metaheuristics, and stochastic modeling. Proficiency in Python and experience with relevant libraries (Pyomo, Pulp, OR-Tools, SciPy). Strong experience building end-to-end platforms or optimization engines deployed in production. Functional understanding of at least one domain: supply chain, logistics, manufacturing, pricing, scheduling, or workforce planning. Excellent communication skills – able to interact with technical and business teams effectively. Experience integrating optimization models into enterprise systems (APIs, cloud deployment, etc.). Preferred Qualifications Exposure to cloud platforms (AWS, GCP, Azure) and MLOps pipelines. Familiarity with data visualization (Dash, Plotly, Streamlit) to present optimization results. Certification or training in operations research or mathematical optimization tools. Show more Show less

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

About us At ExxonMobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world’s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for. The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies. We invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs. Learn more about our What and our Why and how we can work together . What role you will play in our team Operations Research Engineers function as internal consultants to support improved decision-making by developing models using operations research methods, such as mathematical optimization and stochastic simulation. They will work in a team environment to apply their technical skills, project management, and business domain knowledge to develop technological and analytics solutions in partnership with business units to influence and improve key business decisions. The Operations Research Engineer is expected to work with global, cross-functional stakeholders to understand business problems (both commercially and technically), translate them into mathematical problems, and apply operations research methods to create solutions for decision support. This role will primarily work on business problems related to supply chain and commercial functions, especially for Fuels, Lubes, and Chemical products. What you will do Participate in the scoping of business problems to apply operations research methods Work with key contacts to identify and translate data requirements which represent the system and constraints to be modeled Develop custom mathematical optimization and/or stochastic simulation models by applying the following: linear programming, mixed-integer programming, system dynamics simulation, and/or discrete event simulation Proactively drive cross-functional alignment across organizations (as needed) to validate model solution quality Create documentation to explain how the operations research methods are applied, and conduct reviews with senior technical professionals to ensure technical quality Ensure effective and efficient pace of work by managing project timelines, coordinating project team members, and providing timely updates to stakeholders Work effectively within cross-functional, global teams (including business domain experts, product owners, decision science engineers, and IT) to design, develop, deploy, and sustain operations research-based solutions that are scalable and with commercial-grade quality About You Skills and Qualifications Bachelors or Master’s degree preferred in Industrial Engineering or Applied Mathematics (or relevant field) Ability to translate general requirements and long-term deadlines into shorter-term work tasks, self-direct work, and monitor progress Solicts inputs from subject matter experts (SMEs) and engages with cross-functional teams to drive results Strong analytical skills with 2+ years’ experience in applying operations research modeling methods (mathematical optimization and/or stochastic simulation) for commercial-grade quality solutions Competent in developing mathematical optimization models using mathematical modeling languages such as AIMMS, GAMS, AMPL, Pyomo, Gurobipy, etc. Competent in developing system dynamics simulation models using software such as Stella Architect, VenSim, AnyLogic, etc. 5+ years’ experience in applying operations research modeling methods (mathematical optimization and/or stochastic simulation) for commercial-grade quality solutions Curious mindset in understanding business problems and their related factors to develop solutions Ability to view complex subjects from both a high level and detailed perspective, and communicate appropriately with different audiences Skills and Qualifications Familiarity with developing discrete event simulation models using software such as Arena, Simio, etc. Familiarity with Python, especially for developing and deploying operations research solutions Experience with source code version control (Git) Strong written and verbal communication skills Your benefits An ExxonMobil career is one designed to last. Our commitment to you runs deep our employees grow personally and professionally, with benefits built on our core categories of health, security, finance and life. We offer you: Competitive compensation Medical plans, maternity leave and benefits, life, accidental death and dismemberment benefits Retirement benefits Global networking & cross-functional opportunities Annual vacations & holidays Day care assistance program Training and development program Tuition assistance program Workplace flexibility policy Relocation program Transportation facility Please note benefits may change from time to time without notice, subject to applicable laws. The benefits programs are based on the Company’s eligibility guidelines. Stay connected with us Learn more about ExxonMobil in India, visit ExxonMobil India and Energy Factor India . Follow us on LinkedIn and Instagram Like us on Facebook Subscribe our channel at YouTube EEO Statement ExxonMobil is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin or disability status. Business solicitation and recruiting scams ExxonMobil does not use recruiting or placement agencies that charge candidates an advance fee of any kind (e.g., placement fees, immigration processing fees, etc.). Follow the LINK to understand more about recruitment scams in the name of ExxonMobil. Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship. Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. 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What success looks like in this role: Mathematical Modelling & Optimization Analyse complex business and industrial challenges and translate them into mathematical optimisation models. Develop linear, nonlinear, mixed-integer programming (MIP), constraint programming (CP), and graph-based models to address large-scale combinatorial issues. Implement models using AMPL, Gurobi, CPLEX, Pyomo, or specialised solvers for benchmarking and testing. Explore hybrid quantum-classical algorithms for optimisation, collaborating with experts in quantum computing. Develop and apply metaheuristic optimisation techniques such as Genetic Algorithms, Simulated Annealing, and Ant Colony Optimisation to tackle large-scale, complex business challenges. Integration of Hybrid Advanced Metaheuristic and HPC Collaborate closely with our Quantum and HPC R&D teams to identify high-value combinatorial problems where quantum computing can offer a computational advantage. Develop proof-of-concept (PoC) studies that compare classical optimisation techniques with quantum/hybrid approaches. Work with software developer solution engineers to integrate HPC-powered solvers for large-scale combinatorial optimisation problems. Industry Applications & NextGen Advisory Develop decision support systems and prescriptive analytics solutions for clients in finance, logistics, cybersecurity, and smart infrastructure. Provide leadership and contribute to white papers, patents, and publications on innovative quantum optimisation methodologies. You will be successful in this role if you have: BA/BS degree and 0-2 years’ relevant experience OR equivalent combination of education and experience Unisys is proud to be an equal opportunity employer that considers all qualified applicants without regard to age, blood type, caste, citizenship, color, disability, family medical history, family status, ethnicity, gender, gender expression, gender identity, genetic information, marital status, national origin, parental status, pregnancy, race, religion, sex, sexual orientation, transgender status, veteran status or any other category protected by law. This commitment includes our efforts to provide for all those who seek to express interest in employment the opportunity to participate without barriers. If you are a US job seeker unable to review the job opportunities herein, or cannot otherwise complete your expression of interest, without additional assistance and would like to discuss a request for reasonable accommodation, please contact our Global Recruiting organization at GlobalRecruiting@unisys.com or alternatively Toll Free: 888-560-1782 (Prompt 4). US job seekers can find more information about Unisys’ EEO commitment here .

Job Title: Optimization Scientist – Route & Inventory Optimization (OR & RL) Location: Hyderabad (On-site) Experience Required: 1+ year Company Overview: We are a leading AI-driven supply chain solutions company focused on transforming retail, FMCG, and logistics through cutting-edge technologies in machine learning, operations research, and reinforcement learning. Our mission is to build intelligent systems that enhance decision-making and automate processes across forecasting, inventory, and transportation. Internship Overview: We are seeking a passionate and motivated AI/ML Intern to support the development of intelligent optimization systems for route planning and inventory allocation. You will work alongside experienced scientists and engineers, gaining hands-on experience in applying machine learning, reinforcement learning, and operations research to real-world logistics challenges. Key Responsibilities: 🔹 Assist in Route Optimization Projects: Support in modeling and solving simplified versions of Vehicle Routing Problems (VRP) under guidance. Work with Python libraries like Pyomo or OR-Tools to prototype optimization solutions. Explore reinforcement learning methods (e.g., DQN, PPO) for dynamic routing decisions under uncertainty. 🔹 Support Inventory Optimization Efforts: Learn to model multi-echelon inventory systems using basic OR and simulation techniques. Analyze historical data to understand stock levels, service times, and demand variability. Help design experiments to evaluate replenishment strategies and stocking policies. 🔹 Contribute to AI-Driven Decision Systems: Assist in integrating ML forecasting models with optimization pipelines. Participate in the development or testing of simulation environments for training RL agents. Collaborate with the team to evaluate model performance using historical or synthetic datasets. Required Qualifications: Currently pursuing or recently completed a degree in Computer Science, Data Science, Operations Research, Industrial Engineering, or related field. Good understanding of Python and key libraries (NumPy, Pandas, Matplotlib, Scikit-learn). Familiarity with basic optimization concepts (LP/MILP) and libraries like OR-Tools or Gurobi (student license). Basic knowledge of reinforcement learning frameworks (OpenAI Gym, Stable-Baselines3) is a plus. Strong problem-solving skills and willingness to learn advanced AI/OR techniques. What You’ll Gain: Hands-on exposure to real-world AI and optimization use cases in logistics and supply chain. Mentorship from experienced scientists in OR, ML, and RL. Experience working in a fast-paced, applied research environment. Opportunity to convert to a full-time role based on performance and business needs. About WINIT: WINIT is a pioneer in mobile Sales Force Automation (mSFA) with over 25 years of experience. We serve more than 600 global enterprises, helping them enhance efficiency, streamline logistics, and leverage AI/ML to optimize sales operations. With a commitment to innovation and global support, WINIT continues to lead digital transformation in sales. Show more Show less

What You’ll Do If you desire to be part of something special, to be part of a winning team, to be part of a fun team - winning is fun. In Eaton, making our work exciting, engaging, meaningful; ensuring safety, health, wellness; and being a model of inclusion & diversity are already embedded in who we are - it’s in our values, part of our vision, and our clearly defined aspirational goals Eaton’s Research Labs (ERL) is a global research team and has an exciting and rewarding position for a Power System Engineer seeking a challenging career in Power System and Energy industry. This position enables the person hired to develop new technologies, improve existing products, acquire internal and external funding, lead discussions with customer technology leaders, present ideas and projects to Eaton business leaders and ERL leadership. A good blend of technical knowledge and business acumen is desired to be successful in this role. The selected candidate will be working with engineering teams located at EIIC Pune and collaborate with different teams and businesses at various locations. We are looking for a Senior Specialist Engineer to lead our team in the research area of Renewable Integration focusing on power systems controls, protection and health monitoring. Responsibilities The Senior Specialist is expected to serve as a technology expert overseeing multiple technology themes within the Energy Systems team. Responsible for driving the strategy for themes and executing multi-year roadmaps to meet business needs. Perform research on power system controls, devices/ system reliability, power system protection, fault location, isolation, and system restoration (FLISR), health monitoring of power grid assets. Bring together state-of-the-art power systems engineering methods, physics-of-failure/ electrical faults, data acquisition and analytics, mathematical modeling, and simulation tools to validate protection schemes, develop advanced control solutions to improve the reliability, economics and sustainability through maximizing renewable integration, offering ancillary services, aggregator platforms and VPP. Drive multidisciplinary research projects in close collaboration with stake holders including business units, COE’s, as well as external universities and industrial partners. Record research findings and file patents, trade secrets and write technical reports. Qualifications Ph.D. or Master’s in electrical/ Electronics/ Power Systems/ Controls Engineering/ or equivalent technical field from accredited institutions. Ph.D. (15 - 18 years) experience or Masters with (18 – 20) years’ experience in power systems technologies focused on distributed energy resource management, micro grids, smart-grids, grids of future, power converters, connected systems, distribution system protection, asset health management and smart products. Skills Experience in battery degradation modelling and predictive controls is desirable. Hands-on experience in electrical power systems, distributed energy resources, VPP, aggregator platforms, integration of renewables, protection in traditional grids, smart grids and grids with renewables, power electronic converters, grid interface devices. Should have strong technical background and experience in Power systems such as implementation of advanced protection schemes, for autonomous & resilient grid applications. Experienced in a variety of power system protection, monitoring and control (FLISR, AMI, integrated Volt/VAR control, adaptive protection, etc.) Experience in developing solutions for power system devices (Relays, CB’s, reclosers, voltage regulators, capacitor banks, network protectors, fuse) is required. Working experience in developing algorithms, performing engineering analytics, system modeling and hardware-in-loop studies for power system protection for both in front of meter and behind the meter applications is a must. Possess strong business acumen and the ability to understand and formulate compelling value propositions and to understand and drive through value and adoption chain. Understanding of mechanical systems and electromechanical actuators will be desirable. Proven track record for IP generation and publications in reputed peer-reviewed journals is desired. Hands-on experience with engineering tools like MATLAB/Simulink, PSCAD, RTDS, TYPHOON HIL, OPALRT and experience in building experimental setups and conducting disciplined experiments would be desired. Software development capability: python, C and C++, PYOMO. Ability to mentor and coach junior engineers and interns is required. Should be able to work with cross functional teams and partner with National Labs and Universities. Ability to apply Design for Six Sigma methodologies including QFD, DoE and reliability engineering in the course of their work. Green belt certification in DFSS or DMAIC is highly desired. Experience in leading programs with multiple stakeholders in matrix organization and strong project management experience is required. ]]> Show more Show less

Location: Bengaluru, KA, IN Company: ExxonMobil About us At ExxonMobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world’s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for. The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies. We invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs. Learn more about our What and our Why and how we can work together . What role you will play in our team Operations Research Engineers function as internal consultants to support improved decision-making by developing models using operations research methods, such as mathematical optimization and stochastic simulation. They will work in a team environment to apply their technical skills, project management, and business domain knowledge to develop technological and analytics solutions in partnership with business units to influence and improve key business decisions. The Operations Research Engineer is expected to work with global, cross-functional stakeholders to understand business problems (both commercially and technically), translate them into mathematical problems, and apply operations research methods to create solutions for decision support. This role will primarily work on business problems related to supply chain and commercial functions, especially for Fuels, Lubes, and Chemical products. What you will do Participate in the scoping of business problems to apply operations research methods Work with key contacts to identify and translate data requirements which represent the system and constraints to be modeled Develop custom mathematical optimization and/or stochastic simulation models by applying the following: linear programming, mixed-integer programming, system dynamics simulation, and/or discrete event simulation Proactively drive cross-functional alignment across organizations (as needed) to validate model solution quality Create documentation to explain how the operations research methods are applied, and conduct reviews with senior technical professionals to ensure technical quality Ensure effective and efficient pace of work by managing project timelines, coordinating project team members, and providing timely updates to stakeholders Work effectively within cross-functional, global teams (including business domain experts, product owners, decision science engineers, and IT) to design, develop, deploy, and sustain operations research-based solutions that are scalable and with commercial-grade quality About You Skills and Qualifications Bachelors or Master’s degree preferred in Industrial Engineering or Applied Mathematics (or relevant field) Ability to translate general requirements and long-term deadlines into shorter-term work tasks, self-direct work, and monitor progress Solicts inputs from subject matter experts (SMEs) and engages with cross-functional teams to drive results Strong analytical skills with 2+ years’ experience in applying operations research modeling methods (mathematical optimization and/or stochastic simulation) for commercial-grade quality solutions Competent in developing mathematical optimization models using mathematical modeling languages such as AIMMS, GAMS, AMPL, Pyomo, Gurobipy, etc. Competent in developing system dynamics simulation models using software such as Stella Architect, VenSim, AnyLogic, etc. 5+ years’ experience in applying operations research modeling methods (mathematical optimization and/or stochastic simulation) for commercial-grade quality solutions Curious mindset in understanding business problems and their related factors to develop solutions Ability to view complex subjects from both a high level and detailed perspective, and communicate appropriately with different audiences Skills and Qualifications Familiarity with developing discrete event simulation models using software such as Arena, Simio, etc. Familiarity with Python, especially for developing and deploying operations research solutions Experience with source code version control (Git) Strong written and verbal communication skills Your benefits An ExxonMobil career is one designed to last. Our commitment to you runs deep our employees grow personally and professionally, with benefits built on our core categories of health, security, finance and life. We offer you: Competitive compensation Medical plans, maternity leave and benefits, life, accidental death and dismemberment benefits Retirement benefits Global networking & cross-functional opportunities Annual vacations & holidays Day care assistance program Training and development program Tuition assistance program Workplace flexibility policy Relocation program Transportation facility Please note benefits may change from time to time without notice, subject to applicable laws. The benefits programs are based on the Company’s eligibility guidelines. Stay connected with us Learn more about ExxonMobil in India, visit ExxonMobil India and Energy Factor India . Follow us on LinkedIn and Instagram Like us on Facebook Subscribe our channel at YouTube EEO Statement ExxonMobil is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin or disability status. Business solicitation and recruiting scams ExxonMobil does not use recruiting or placement agencies that charge candidates an advance fee of any kind (e.g., placement fees, immigration processing fees, etc.). Follow the LINK to understand more about recruitment scams in the name of ExxonMobil. Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship. Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. 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