2 Solvers Jobs

As an Optimization Specialist, you will be responsible for building and scaling mathematical models and process optimization. Your role will involve designing and implementing optimization models such as LP, MIP, and MILP for real-world scheduling, routing, and planning scenarios. Additionally, you will be expected to construct simulation models to evaluate performance under uncertainty, collaborate with cross-functional teams to refine problem definitions, and translate them into quantitative models. You will work closely with data scientists, software engineers, and business analysts to drive predictive optimization workflows using AI/ML algorithms for forecasting, clustering, and classification. Conducting what-if analyses and sensitivity testing to support decision-making will be a crucial part of your responsibilities. Furthermore, you will support research and pilot initiatives involving Quantum-Inspired Optimization (QUBO, hybrid models) and present findings and model performance to stakeholders through clear and concise visualizations and documentation. To excel in this role, you must possess a strong knowledge of Linear Programming (LP), Mixed Integer Programming (MIP/MILP), Constraint Programming, and have experience formulating and solving large-scale combinatorial problems. Hands-on experience with Optimization libraries like Pyomo, PuLP, and solvers such as CPLEX, Gurobi, GLPK, or CBC will be beneficial. Proficiency in programming languages like Python, R, or MATLAB is essential, along with simulation expertise in tools like SimPy, AnyLogic, Arena, or equivalent for discrete-event or agent-based simulation. Your educational background should include a PhD in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or a related field. Additionally, applied machine learning knowledge including forecasting models, clustering, and model evaluation metrics (e.g., MAPE, RMSE) will be advantageous. Strong communication and documentation skills are necessary to effectively present models and insights to non-technical audiences.,

SENIOR OPTIMIZATION ENGINEER Hyderabad Role Senior Optimization Engineer Contract type Permanent About the role As a Senior Optimization Engineer you provide technical expertise in the area of numerical optimization of thermo-fluid systems which are core to the Company's business this includes trade-off and optimize energy efficiency, production cost and operating economy. You engage with global product teams to solicit business needs and convert those into computational decision-making workflows, methods and tools to radically impact how company's products are designed, deployed and operated. Key targets include improving engineering effectiveness as well as developing disruptive, innovative methods for model-based design and operation of company's systems. You also take active part in product development to support design engineers in adopting and using new methods and tools. You also work closely with other teams in Systems, Controls, ML/AI COE, including teams responsible for model development (to drive the development of optimization-friendly thermo-fluid models) and controls engineering (to promote the use of computational optimization strategies (MPC, RTO) as needed). We are offering you We are committed to offering competitive benefits programs for all of our employees and enhancing our programs when necessary. A dynamic and international work environment in a company with high technology products. A strong growth strategy and people who are passionate about what they do. Requirements Education MEng or PhD in a relevant Engineering discipline (e.g., applied mathematics, mechanical or chemical engineering) with 5+ years of experience. Skills and qualifications Proven ability to capture engineering design and operation problems as mathematical programming problems (NLPs), including attention to reliable convergence of such problems. Proficient with the mathematical theory (applied mathematics, numerical analysis and functional analysis), algorithmic foundations (notably existence and convergence proofs), and methods/tools for numerical optimization (SQP, interior point method, etc.) of large-scale systems. Experience from using common algorithms/solvers for large-scale gradient-based non-linear programs, e.g., IPOPT, CONOPT, KNITRO, and WORHP, including their respective applicability to different types of problems. Experience from formulating and solving discrete optimization problems and using common algorithms, including CPLEX and Gurobi. Familiarity with physics-based modeling principles and best practices of thermo-fluid systems, such as vapor compression cycles or power plants. Familiarity and experience with development of computational platforms and tools in Python or equivalent. Familiarity with using HPC and cloud-based platforms for computation at scale. Demonstrated ability to work as part of a multidisciplinary team and an entrepreneurial attitude towards technological innovation in a global environment. Self-starter who is well-organized in an international team environment, with proven communication skills. Responsibilities Deployment. Support that methods and tools developed in the group impact the company's business through engagement in global product projects, including capture and formulation of computational problems arising in such projects. Methods, tools and algorithms. Ensure that appropriate computational methods, tools and algorithms for large-scale numerical optimization are based on sound mathematical foundations and are deployed to match the needs of the company's business, including contributing to the architecture, development, testing and documentation of the methods and tools developed in the group. Modeling for optimization. Support development of mathematical models for thermo-fluid systems are built based on principles and best practices that secure reliable application of numerical optimization algorithms. Talent. Support development and training of staff within company's product teams and within the Computational Engineering group; contribute to talent pipeline by supervising student internships and theses.