Develop and implement sophisticated optimization algorithms for energy storage and distribution
Design and create new customer-facing features to enhance user experience
Apply machine learning techniques to improve load and solar forecasting
Define, develop, and maintain monitoring and simulation systems to proactively identify and diagnose performance issues
Oversee the complete software deployment lifecycle, including writing production-level code, conducting comprehensive testing and validation, and managing the deployment process
Collaborate with cross-functional teams to seamlessly integrate algorithms into Tesla’s ecosystem
Perform rigorous testing and validation to ensure the accuracy and robustness of solutions
Clearly communicate complex technical concepts and results to non-technical stakeholders
Provide technical insights to guide product development and support business development strategies
What You’ll Bring
Degree in Mathematics, Statistics, or a related field with a focus on numerical optimization, operations research, or equivalent experience
Strong proficiency in Python and Linux environments; additional expertise in Go and Rust is highly valued
Proven experience in developing real-world products and solutions using numerical optimization techniques such as LP, MILP, and nonlinear optimization, with expertise in solvers like Gurobi, XPRESS, GLPK, or CPLEX
Background in researching, developing, and deploying innovative algorithmic strategies for novel optimization challenges, including decision-making under uncertainty, scenario optimization
Experience in machine learning, time-series forecasting, and analysis
Experience with battery control systems or similar control technologies
Demonstrated experience in deploying code to production environments
Familiarity with cloud and big data technologies, including Spark, Airflow, AWS, Docker, and Kubernetes
Excellent communication skills with the ability to thrive in a team-oriented environment
Experience in sustainability and clean energy solutions