Sr. Machine Learning Engineer, Energy Optimization

As a Senior Machine Learning Engineer focused on Energy Optimization, you will help build and productionize applied machine learning models inside Tesla’s Opticaster platform. The work centers on improving battery charging and discharging decisions using forecasting and evaluation practices that support reliable operation at residential scale.

Opticaster’s mission is to accelerate the world’s transition to sustainable energy by optimizing when batteries store and release energy to maximize value for customers and the grid. With a global fleet of over 500,000 residential systems, the platform requires robust, production-grade machine learning that can be validated, monitored, and safely rolled out.

Responsibilities

• Develop, improve, and productionize machine learning components in Opticaster, including time-series forecasting for inputs such as load and solar, and other models that feed battery dispatch
• Use ML and related techniques to improve Opticaster’s energy decisions in production
• Implement model and algorithm updates in the Opticaster codebase, including production Python, tests, and collaboration on safe rollout and firmware or release coordination
• Create and maintain evaluation pipelines, including offline metrics, simulation, benchmarking, and regression detection to quantify ML impact and identify regressions before release
• Diagnose field and simulation failures, separating model and data issues from interface or integration problems
• Improve observability for production ML, including monitoring, alerting, and tooling that helps explain model behavior across the fleet
• Identify and resolve performance bottlenecks in ML pipelines, including CPU, memory, latency, and constrained on-device or runtime paths
• Partner with algorithm, software, firmware, and product engineers to integrate machine learning into Tesla’s residential energy ecosystem

Requirements

• Degree in Computer Science, Engineering, Statistics, or a related technical field (or equivalent experience)
• Strong proficiency in Python, with the ability to work effectively in a large existing codebase
• Experience shipping applied machine learning into production systems, including training, evaluation, deployment, and ongoing operation; time-series forecasting experience is a plus
• Experience owning production software end to end, with emphasis on correctness, performance, and maintainability
• Experience validating model changes using offline metrics, simulation, or regression-style evaluation against real data
• Experience with cloud and data technologies such as AWS, Spark, Airflow/Argo (or equivalent orchestration), Docker/Kubernetes, and CI/CD
• Excellent communication skills and experience collaborating across algorithm, software, firmware, and product partners
• Rust experience is a plus
• Experience with energy systems, battery storage, or similar real-world control systems is a plus

Technologies

• Python
• AWS
• Spark
• Airflow/Argo
• Docker
• Kubernetes
• CI/CD

What to Expect

• Opticaster optimizes battery charge and discharge timing by considering electricity prices, solar generation, and grid conditions
• These optimizations support Tesla’s energy products, including Megapacks, Powerwalls, Virtual Power Plants, and microgrids
• Opticaster supports grid stability through programs such as demand response and integrates with Autobidder to participate in electricity markets
• As a Machine Learning Engineer on Opticaster, you will own applied ML models, including time-series forecasting for load and solar, and other models that guide energy decisions in the field
• You will develop models, improve evaluation and monitoring, and ship them to production so they scale across the fleet

Location and Salary

• Location: Palo Alto, CA (onsite)
• Salary: USD 140,000 - 312,000 per year

Expected Compensation

• $140,000 - $312,000/annual salary + cash and stock awards + benefits
• Pay offered may vary based on market location and job-related knowledge, skills, and experience
• Total compensation may include other elements depending on the position offered

Benefits

• Medical plans with options including $0 payroll deduction
• Family-building, fertility, adoption, and surrogacy benefits
• Dental (including orthodontic coverage) and vision plans with options including $0 paycheck contribution
• Company paid HSA contribution when enrolled in the High-Deductible medical plan with HSA
• Healthcare and Dependent Care Flexible Spending Accounts (FSA)
• 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
• Company paid Basic Life and AD&D
• Short-term and long-term disability insurance (90 day waiting period)
• Employee Assistance Program
• Sick and Vacation time (Flex time for salary positions, accrued hours for hourly positions) and Paid Holidays
• Back-up childcare and parenting support resources
• Voluntary benefits including critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
• Weight Loss and Tobacco Cessation Programs
• Tesla Babies program
• Commuter benefits
• Employee discounts and perks program
• Earned Wage Access: real-time pay access paid daily, subject to eligibility and schedule (applicable for below Sr. Managers levels)