Senior Optimization Engineer

Fluence is the leading global energy storage technology and services company, created and backed by Siemens and AES, two industry powerhouses and pioneers in energy storage. Fluence unites the scale, experience, breadth, and financial backing of the two most experienced icons in energy storage.

Our mission is to create a more sustainable future by transforming the way we power our world. Energy storage is critical to this transformation, yet today the market is fragmented and customers face the challenge of finding a trusted technology partner amidst conflicting technical claims, inexperienced vendors and installers, and new market entrants with limited power sector knowledge.

Fluence brings the proven technology solutions and services that overcome the commercial and regulatory barriers that stand in the way of modernizing our energy networks. We are the partner that can deliver at a global scale with the most experienced and knowledgeable team in the world.

This position is within the Fluence Digital business unit, formed following Fluence’s acquisition of San Francisco-based start-up AMS. Fluence Digital’s software technology leverages artificial intelligence, advanced price forecasting, portfolio optimization, and market bidding to ensure energy storage and flexible generation assets respond optimally to market dynamics across global electricity markets.

As a Senior Optimization Engineer, you will provide technical leadership and collaborate with cross-functional teams to enhance and guide our market-leading optimization and bidding product, Mosaic, which is designed for renewable energy and battery storage assets in electricity markets across the globe. You will identify the most impactful projects, address challenges proactively, and successfully deliver key initiatives. Additionally, you will mentor and coach team members across the Optimization, Forecasting, and Analytics teams.

Key responsibilities include:

•Optimization Model Development: Translate market rules into asset scheduling and dispatch optimization models, ensuring compliance and efficiency in bidding and dispatch operations. 

•Forecast Integration: Partner with the Forecasting team to define requirements for generating probabilistic Energy, Ancillary Service, and other electricity market price forecasts, integrating them seamlessly into optimization workflows.

•Data Preparation and Integration: Develop processes to read and transform market data and asset information into formats suitable for optimization models, and ensure that optimization outputs are transformed and stored according to database schemas.

•Optimization Performance Analysis: Conduct in-depth analysis of daily optimization results to identify potential enhancements in algorithmic strategies. Continuously evaluate and adapt the optimization approach to align with evolving market dynamics, ensuring the platform remains agile and maximizes revenue opportunities for customers under emerging price regimes and market conditions. Leverage insights to proactively refine bidding strategies and maintain a competitive edge in global electricity markets.

•Platform Improvement: Collaborate with other Optimization Engineers to continuously enhance and maintain Fluence’s Mosaic market bidding platform for battery storage and renewable assets in global electricity markets.

•Software Development Best Practices: Evangelize and implement software development best practices, including version control, CI/CD, and testing frameworks, to improve the scalability and maintainability of optimization applications.

•Model Deployment: Create, deploy, and optimize containerized solutions for scalable optimization environments. Leverage platforms such as Kubernetes to ensure efficient and reliable deployment of optimization models.

•Infrastructure and Automation: Design and implement CI/CD pipelines for automated model and code deployment, ensuring reliable and repeatable workflows for testing and production rollouts (e.g., CircleCI).

•Performance Optimization: Monitor and refine deployed models and workflows to ensure high reliability, scalability, and optimal performance, addressing evolving requirements as needed.

•Collaboration and Integration: Work closely with cross-functional teams, including data scientists, engineers, and product stakeholders, to integrate optimization systems effectively into broader applications.

•Team Leadership and Culture: Model and cultivate a culture of inclusivity, trust, exceptional communication, collaboration, respect, continuous learning, and enthusiasm for innovation and problem-solving.

What Will Our Ideal Candidate Bring to Fluence?

•Experience: 8+ years of industry experience developing optimization models, preferably to address bidding and dispatch challenges in electricity markets.

•Electricity Market Design Expertise: Comprehensive knowledge of electricity market structures and bid optimization strategies across global markets, including the nuances of market design variations in the US, Europe, Australia, and beyond.

•Energy Industry Knowledge: In-depth knowledge of the energy industry, with expertise in deregulated electricity markets such as CAISO, ERCOT, MISO, PJM, NEM, and Japan.

•Optimization and Software Development: Experience deploying optimization models written in Python to production, using commercial solvers (e.g., Gurobi, Xpress, CPLEX) and following software development best practices such as version control, CI/CD, and testing.

•Stochastic and Convex Optimization: Strong comprehension of stochastic optimization within the realm of energy systems and familiarity with convex optimization methodologies, including linearization techniques.

•Risk Management and Hedging Expertise: Profound understanding of risk management principles and strategies to mitigate price volatility and uncertainty across sequential markets. Experience designing and implementing hedging techniques that optimize revenue while minimizing exposure to market risks  to ensure robust decision-making under uncertainty.

•Programming Skills: Advanced proficiency in Python for developing, deploying, and maintaining optimization models, and familiarity with containerization tools and orchestration platforms like Kubernetes.

•Collaboration: Demonstrated ability to collaborxate with cross-functional teams and build strong working relationships.

•Agile/Lean Product Development: Experience working and delivering products or services in an agile/lean environment.

•Communication: Excellent communication skills, with the ability to clearly articulate complex technical concepts to diverse audiences.

•Education: An advanced degree (Master’s or PhD) in Operations Research, Computer Science, Electrical Engineering, or a related field is preferred.

•Additional Expertise: Familiarity with using game-theoretic models to inform decision-making processes is a plus.