Optimization and ML Modelling Engineer

Location: Bengaluru, Karnataka   About the Company:  Sustainability Economics.ai is a global organization, pioneering the convergence of clean energy and AI, enabling profitable energy transitions while powering end-to-end AI infrastructure. By integrating AI-driven cloud solutions with sustainable energy, we create scalable, intelligent ecosystems that drive efficiency, innovation, and long-term impact across industries. Guided by exceptional leaders and visionaries with decades of expertise in finance, policy, technology, and innovation, we are committed to making long-term efforts to fulfil this vision through our technical innovation, client services, expertise, and capability expansion.  Role Summary:  We are seeking a highly skilled Optimization and Modelling Engineer to design, develop, and deploy prescriptive models that identify optimal solutions under complex business and operational constraints. The role focuses on formulating and solving optimization problems using advanced mathematical programming and numerical methods. The ideal candidate will combine strong analytical thinking with hands-on Python development to build models that drive intelligent, data-informed decision-making. Key Responsibilities:  Design, develop, and implement optimization and forecasting models for complex analytical problems. Apply mathematical programming (linear, nonlinear, integer, and mixed-integer optimization) to operational and decision-making scenarios. Build, train, and fine-tune machine learning and statistical models for regression, classification, and clustering. Conduct feature selection, hyperparameter tuning, and performance evaluation using systematic validation techniques. Integrate ML and optimization algorithms within business or system logic for intelligent decision-making. Collaborate with cross-functional teams to ensure models are scalable, interpretable, and production-ready. Stay updated with advancements in optimization algorithms, ML model architectures, and applied AI techniques. Education & Experience: Bachelor’s or Master’s degree in Computer Science, Engineering, Applied Mathematics, or related quantitative fields. 1–2 years of hands-on experience in machine learning, optimization. Strong background in mathematical modeling, statistics, or operations research. Experience in production-grade model deployment and performance monitoring. Skills Required: The candidate should have strong proficiency in Python, with practical experience for building optimization models. Strong proficiency in Python and libraries such as SciPy,Pyomo, NumPy, OR-Tools, PuLP, Gurobi, or CPLEX. A solid understanding of linear programming, mixed-integer programming, convex optimization, stochastic optimization, and constraint programming is essential. The role requires experience in algorithm design, numerical methods, and sensitivity analysis for robust model development. The candidate should possess a strong background in operations research and optimization model formulation. Experience in model validation and performance tuning is required to ensure accuracy and efficiency. The role involves performing scenario analysis and supporting optimization-based decision-making. Knowledge of workflow automation and integration of optimization models with APIs will be an advantage. Proficiency in version control using Git. The candidate should demonstrate strong problem-solving and analytical thinking abilities. Clear documentation skills and the ability to communicate technical results effectively are essential. What You’ll Do: Build and train ML and optimization models for production-scale use cases. Design intelligent data workflows and pipelines to support predictive and prescriptive analytics. Translate business objectives into mathematical formulations that can be optimized effectively. Collaborate with engineering and research teams to develop scalable ML solutions. Develop APIs and tools to make ML capabilities accessible across systems. Continuously monitor, maintain, and enhance model accuracy and scalability.  What you will bring Proven track record of implementing ML and optimization models in production environments. Strong mathematical and statistical foundation. Passion for scalable systems, automation, and applied problem-solving. Startup DNA → bias to action, comfort with ambiguity, love for fast iteration, and flexible and growth mindset.  Why Join Us  Shape a first-of-its-kind AI + clean energy platform. Work with a small, mission-driven team obsessed with impact. An aggressive growth path. A chance to leave your mark at the intersection of AI, Optimization and sustainability.