Principal Energy Storage Software Optimization Engineer - REMOTE
WFA Digital Insight
The demand for renewable energy solutions has skyrocketed, with over 9GW of utility-scale projects launched in recent years. As a result, experts in energy storage software optimization are in high demand. ThinkBAC Consulting, a pioneer in the field, is seeking a Principal Energy Storage Software Optimization Engineer to lead the development of predictive models and drive business growth. With the US renewable energy market expected to grow by 20% annually, this role offers a unique chance to be part of a revolutionary industry shift. Candidates should be prepared to showcase their expertise in machine learning, software optimization, and energy trading.
Job Description
About the Role
The Principal Energy Storage Software Optimization Engineer will play a critical role in developing and implementing quantitative predictive models for utility-scale renewable energy projects. As a key member of the Software, Data, and Technology Team, you will be responsible for driving the algorithmic decision-making process and optimizing energy storage initiatives. The ideal candidate will have a strong background in machine learning, software optimization, and energy trading, with experience working in production-ready coding environments.As a Principal Engineer, you will be part of a creative team focused on energy storage, battery storage energy trading strategies, asset management, and real-time energy pricing. You will work closely with cross-functional teams to develop and implement mixed-integer linear programming (MILP) optimization models, multitasking time series forecast models, and other predictive models.
The company is committed to creating more renewable infrastructure solutions for the grid and is offering comprehensive compensation packages to employees leading the drive to meet company goals.
What You Will Do
- Develop and implement quantitative predictive models for utility-scale renewable energy projects
- Design and test multitasking time series forecast models in AWS Sagemaker machine learning environment
- Utilize forward-thinking techniques such as optimal control, deep learning, machine learning (AI/ML), and reinforcement learning to evaluate and update current protocols
- Drive the implementation of full-lifecycle ML/AI solutions and take ownership of real-time troubleshooting
- Develop, update, and implement mixed-integer linear programming (MILP) optimization models for energy storage, asset management, and energy trading initiatives
- Create and design optimization models to forecast congestion, assess congestion drivers, and assist in locational marginal pricing (LMP) assessments
- Collaborate with cross-functional teams to develop and implement predictive models
- Stay up-to-date with industry trends and emerging technologies in energy storage and software optimization
What We Are Looking For
- 8-10+ years of experience in optimization-based Python programming, mixed-integer linear programming (MILP), stochastic optimization, and predictive modeling
- Machine learning development experience in production-ready coding environments focused on complex projects
- Expertise in Python-based optimization toolkits such as Pyomo, CVXPY, GurobiPy, etc.
- Experience working in APIs and databases like SQL, NoSQL, and RESTful to process and manipulate large datasets
- Solid understanding of convex optimization techniques (Linear/Mixed Integer programming) and time-series forecasting (PostgreSQL, TimescaleDB, InfluxDB)
- Experience working in Amazon Web Services (AWS) Sagemaker Machine Learning platform
- Well-versed in Bitbucket, git, or GitHub
- Strong understanding of machine learning concepts such as classification, deep learning, deep neural networks (DNN), reinforcement learning, and regression problem-solving techniques
Nice to Have
- Experience working in production-ready coding environments in the energy trading or financial trading sector
- Solid understanding of national energy markets and renewable energy principles
- Familiarity with energy storage and battery storage technologies
- Experience with agile development methodologies and version control systems
Benefits and Perks
- Competitive base salary
- Open PTO policy
- Flex work hours
- Comprehensive benefits package
- Opportunity to work with a transparent Executive Leadership Team
- Remote work stipend
- Professional development opportunities
- Access to cutting-edge technologies and tools
How to Stand Out
- To stand out, highlight your experience with Python-based optimization toolkits and machine learning development in production-ready coding environments.
- Make sure to showcase your understanding of convex optimization techniques and time-series forecasting in your portfolio or resume.
- Be prepared to discuss your experience with energy storage and battery storage technologies, as well as your knowledge of national energy markets and renewable energy principles.
- When negotiating salary, consider the company's comprehensive compensation package and benefits, including the open PTO policy and flex work hours.
- Red flags to watch for include lack of transparency from the company or unclear expectations around the role and responsibilities.
- To increase your chances of success, be sure to research the company and the industry, and come prepared with thoughtful questions to ask the interviewer.
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