Optimization and ML Modelling Engineer

Overview

Design and deploy optimization and ML models for clean energy AI platform

Key Responsibilities

• ml modeling
• optimization
• model monitoring
• feature engineering
• api development
• data pipelines

Tasks

-Build and train ML and optimization models for production-scale use cases. -Continuously monitor, maintain, and enhance model accuracy and scalability. -Stay updated with advancements in optimization algorithms, ML model architectures, and applied AI techniques. -Collaborate with engineering and research teams to develop scalable ML solutions. -Build, train, and fine-tune machine learning and statistical models for regression, classification, and clustering. -Collaborate with cross-functional teams to ensure models are scalable, interpretable, and production-ready. -Apply mathematical programming (linear, nonlinear, integer, and mixed-integer optimization) to operational and decision-making scenarios. -Translate business objectives into mathematical formulations that can be optimized effectively. -Design, develop, and implement optimization and forecasting models for complex analytical problems. -Integrate ML and optimization algorithms within business or system logic for intelligent decision-making. -Shape a first-of-its-kind AI + clean energy platform. -Conduct feature selection, hyperparameter tuning, and performance evaluation using systematic validation techniques. -Develop APIs and tools to make ML capabilities accessible across systems. -Design intelligent data workflows and pipelines to support predictive and prescriptive analytics. -The role involves performing scenario analysis and supporting optimization-based decision-making.

Requirements

• python
• git
• gurobi
• optimization
• bachelor’s
• problem solving

What You Bring

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. -Proficiency in version control using Git. -Passion for scalable systems, automation, and applied problem-solving. -Strong background in mathematical modeling, statistics, or operations research. -The candidate should possess a strong background in operations research and optimization model formulation. -Proven track record of implementing ML and optimization models in production environments. -Startup DNA → bias to action, comfort with ambiguity, love for fast iteration, and flexible and growth mindset. -Bachelor’s or Master’s degree in Computer Science, Engineering, Applied Mathematics, or related quantitative fields. -Knowledge of workflow automation and integration of optimization models with APIs will be an advantage. -The candidate should have strong proficiency in Python, with practical experience for building optimization models. -Strong mathematical and statistical foundation. -Strong proficiency in Python and libraries such as SciPy,Pyomo, NumPy, OR-Tools, PuLP, Gurobi, or CPLEX. -1–2 years of hands-on experience in machine learning, optimization. -Clear documentation skills and the ability to communicate technical results effectively are essential. -The candidate should demonstrate strong problem-solving and analytical thinking abilities. -Experience in production-grade model deployment and performance monitoring. -The role requires experience in algorithm design, numerical methods, and sensitivity analysis for robust model development. -Experience in model validation and performance tuning is required to ensure accuracy and efficiency. -A solid understanding of linear programming, mixed-integer programming, convex optimization, stochastic optimization, and constraint programming is essential.

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Benefits

-Work with a small, mission-driven team obsessed with impact. -A chance to leave your mark at the intersection of AI, Optimization and sustainability.

About Sustainability Economics.Ai

-Founded with a vision to drive the transition to a sustainable future through advanced AI technology. -Specializes in leveraging artificial intelligence to optimize economic sustainability across various industries. -Works on projects that aim to reduce environmental impact while promoting growth and resilience in key sectors. -Has provided consulting for energy, water resources, infrastructure, and transport industries globally. -Their AI models help businesses make data-driven decisions for sustainable operations, improving efficiency and profitability. -Notable for their interdisciplinary approach, combining economic modeling with cutting-edge AI and machine learning techniques. -Has collaborated with government agencies, corporations, and NGOs to shape policies and strategies for sustainable development.

Sector Specialisms