About Fluence: Fluence Energy, Inc. (Nasdaq: FLNC) is a global market leader in energy storage products and services, and optimization software for renewables and storage. With a presence in over 47 markets globally, Fluence provides an ecosystem of offerings to drive the clean energy transition, including modular, scalable energy storage products, comprehensive service offerings, and the Fluence IQ Platform, which delivers AI-enabled SaaS products for managing and optimizing renewables and storage from any provider. Fluence is transforming the way we power our world by helping customers create more resilient and sustainable electric grids.
OUR CULTURE AND VALUES
We are guided by our passion to transform the way we power our world. Achieving our goals requires creativity, diversity of ideas and backgrounds, and building trust to effect change and move with speed.
We are Leading
Fluence currently has thousands of MW of energy storage projects operated or awarded worldwide in addition to the thousands of MW of projects managed by our trading platform—and we are growing every day.
We are Responsible
Fluence is defined by its unwavering commitment to safety, quality, and integrity.
We are Agile
We achieve our goals and meet our customer’s needs by cultivating curiosity, adaptability, and self-reflection in our teams.
We are Fun
We value the diversity in thought and experience of our coworkers and customers. Through honest, forthcoming, and respectful communications we work to ensure that Fluence is an inclusive and welcoming environment for all.
ABOUT THE POSITION:
This position will be within the Fluence Digital business unit, formed following Fluence’s acquisition of San Francisco-based start-up AMS. Fluence Digital’s software technology uses artificial intelligence, advanced price forecasting, portfolio optimization and market bidding to ensure energy storage and flexible generation assets are responding optimally to market dynamics.
As a Senior Optimization Engineer, you will provide technical leadership and partner with cross-functional teams to develop and guide our market-leading optimization and bidding product, Mosaic, for renewable energy and battery storage assets in the Australian National Electricity Market (NEM). You will be able to identify the most impactful projects, proactively remove impediments, and successfully drive towards key initiatives. In addition, you will provide mentorship and coaching to other members of the Optimization, Forecasting and Analytics teams.
Key responsibilities and requirements include:
• Work alongside other Optimization Engineers to continually improve and maintain Fluence’s Mosaic market bidding platform for battery storage and renewable assets in the NEM
• Translate market rules into asset scheduling and dispatch optimization models
• Collaborate with forecasting team to define requirements for generation of probabilistic Energy, Ancillary Service and other electricity market price forecasts
• Evangelize and implement software development best practices in optimization and bidding applications
• Work with Software Engineering, product and forecasting teams to design, deploy monitor and improve optimization and bidding model performance
• Model and cultivate a culture of inclusivity, trust, exceptional communication, collaboration, respect, continuous learning, and enthusiasm for our work
What will our ideal candidate bring to Fluence?
• 7+ years of industry experience developing optimization models, preferably in service of solving bidding and dispatch problems for Australia’s National Electricity Market (NEM)
• Knowledge of the energy industry, especially deregulated electricity markets such as NEM
• Working knowledge of software engineering best practices as applied to optimization problems
• Previous experience deploying optimization models written in Python using commercial solvers such as Gurobi, Xpress, CPLEX, etc. to production
• Demonstrated ability to collaborate with cross-functional teams and build solid working relationships
• Experience working and delivering products or services in an agile/lean environment
• Excellent communication skills
• An advanced degree (Masters or PhD) in Operations Research or related field preferred
Nice to haves:
• Familiarity with using game theoretic models to inform decision-making processes is a nice to have
• A solid comprehension of stochastic optimization within the realm of energy systems
• Familiarity with convex optimization methodologies, and linearization techniques
