Optimization Engineer

A rapidly growing global technology company operating at the intersection of energy trading, data science, and renewable optimization is expanding its U.S. team. The firm specializes in the physical and financial optimization of energy storage and renewable generation assets, leveraging advanced modeling and trading systems to maximize performance across key U.S. power markets and accelerate the transition to a low-carbon future.

• ? Position Overview :

Seeking an Optimization Engineer to join the U.S. Data Science team in Austin. This role will design, build, and deploy advanced optimization models that drive performance across energy storage (BESS), trading (DART), portfolio optimization, and congestion management.

The ideal candidate will blend strong technical modeling expertise with a deep interest in energy systems and market dynamics - building scalable, production-ready optimization solutions that directly inform trading and operational decision-making.

• ? Key Responsibilities :
• Design and implement optimization models to enhance the performance of energy storage and renewable assets.
• Integrate ISO market dynamics (PJM, MISO, ERCOT, etc.) into models to optimize dispatch and trading outcomes.
• Collaborate with Software Engineering and DevOps to deploy scalable, production-ready solutions.
• Develop and maintain simulation and backtesting frameworks to evaluate model performance.
• Continuously refine decision-support tools to adapt to evolving market and operational conditions.
• Work cross-functionally with trading, product, and engineering teams to translate research into production-level systems.
• ? Qualifications Needed :
• 3+ years of experience building and deploying optimization or ML systems into production.
• Strong proficiency in Python and numerical libraries (Pandas, NumPy, Polars, etc.).
• Expertise in optimization frameworks (CVXPY, Pyomo, Gurobipy) and applied optimization techniques (linear, MILP, nonlinear).
• Experience with real-time model predictive control or algorithmic decision systems.
• Familiarity with AWS, Docker, Terraform, Git, CI / CD, and orchestration tools (Airflow / Prefect).
• Bachelors in Computer Science, Electrical Engineering, Operations Research, or a related technical discipline.
• ? Preferred Qualifications :
• Experience with power systems modeling (power flow, SCUC, or market simulation).
• Exposure to U.S. power markets (e.g., ERCOT, PJM, MISO) in a trading or analytics environment.
• Knowledge of Battery Energy Storage Systems (BESS) operation and dispatch economics.
• Familiarity with machine learning frameworks (Scikit-learn, PyTorch, XGBoost).
• Experience with data visualization and dashboarding (Plotly, Dash, Streamlit, Superset).
• Masters or PhD in a quantitative or technical field.
• ? Why Join :

This is an opportunity to work at the cutting edge of optimization, renewable energy, and data science - helping build the infrastructure that powers a sustainable energy future. Youll collaborate with world-class experts, deploy real-world optimization systems, and make measurable impact in global power markets.