Sr. Software & Machine Learning Engineer, Energy Optimization

Tesla is seeking a Sr. Software & Machine Learning Engineer for its Energy Optimization team in Palo Alto, CA. The role involves developing scalable machine learning models and software systems to optimize energy storage and grid management. Key responsibilities include enhancing applications, optimizing deployment processes, and collaborating with cross-functional teams. Candidates should have a degree in Computer Science or Engineering, strong Python skills, and experience with cloud technologies and CI/CD pipelines.
What To Expect
Opticaster’s mission is to accelerate the world’s transition to sustainable energy by optimizing how batteries are charged and discharged to maximize value for customers and the grid. Our advanced algorithms determine the best times to store and use energy, considering electricity prices, solar generation, and grid conditions. These optimizations power Tesla’s energy products, including Megapacks, Powerwalls, Virtual Power Plants, and microgrids. With a global fleet of over 500,000 residential systems, our software operates at scale, requiring robust and efficient solutions. Opticaster also plays a key role in supporting grid stability through programs like demand response and by integrating with Autobidder to actively participate in energy markets.

As a Software Engineer, you will be instrumental in developing and maintaining the software systems that power Tesla’s residential energy solutions. You will work on creating scalable, efficient software architecture tailored for predictive analytics, forecasting, and data-driven decision systems, ensuring seamless integration with Tesla’s energy products. While expertise in algorithmic optimization and machine learning modeling is a plus, the primary focus will be on delivering high-quality machine learning solutions that enhance the efficiency, reliability, and scalability of Tesla’s energy ecosystem. This is your opportunity to drive the future of sustainable energy by working on cutting-edge technologies that leverage machine learning to solve complex challenges in energy storage and grid management.

What You'll Do

Develop and maintain scalable machine learning models and algorithms for energy storage forecasting, demand modeling, and system optimization, including demand response and grid integrationDesign and implement new features to enhance customer-facing applications and improve user experienceOptimize deployment processes through CI/CD, containerization, and infrastructure management, ensuring smooth operations and efficient updatesCollaborate with cross-functional teams to integrate software systems into Tesla’s ecosystem, ensuring seamless deployment and operationBuild and maintain robust software pipelines for training, evaluating, and deploying ML models in production, ensuring reliability and efficiencyContribute to the development and maintenance of monitoring and simulation systems to ensure software reliability and scalabilityProactively identify and resolve performance bottlenecks related to infrastructure, memory, and runtime efficiencyCommunicate technical concepts clearly to non-technical stakeholders to align development with business objectives


What You'll Bring

Degree in Computer Science, Engineering, or equivalent experienceStrong proficiency in Python and Linux environments; experience with Go or Rust is a plusProven experience in developing and deploying scalable software systems, including writing production-level code and ensuring performance in real-world environmentsExperience with cloud and big data technologies such as AWS, Spark, Airflow, and KubernetesExperience with CI/CD pipelines (e.g., GitHub Actions) and automating software deployment processesFamiliarity with optimization techniques, machine learning, and time-series forecasting is highly valuedExcellent communication skills and the ability to collaborate within cross-functional teamsExperience in energy solutions, battery control systems, and a passion for sustainability and clean energy solutionsPractical experience in optimization techniques, time-series forecasting, and machine learning model development, with a focus on energy storage and grid applications is a plusExperience managing containerized applications in embedded or firmware environments, and optimizing resource usage (e.g., memory, CPU) for efficient performance in constrained systems is a plus


Benefits
Compensation and Benefits
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
Medical plans > plan options with $0 payroll deduction Family-building, fertility, adoption and surrogacy benefits Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution Company Paid (Health Savings Accounts) 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, 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 to include: 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


Expected Compensation

$140,000 - $300,000/annual salary + cash and stock awards + benefits

Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

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