Sr. Software & Machine Learning Engineer, Energy Optimization

Responsibilities

• Develop and maintain scalable machine learning models and algorithms for energy storage forecasting, demand modeling, and system optimization, including demand response and grid integration.
• Design and deliver new features for customer‑facing applications to improve the user experience.
• Streamline deployment workflows through CI/CD, containerization, and infrastructure management to ensure reliable operations and efficient updates.
• Collaborate with cross‑functional teams to integrate software components into Tesla’s ecosystem for seamless deployment and operation.
• Build and maintain robust pipelines for training, evaluating, and deploying ML models in production, ensuring reliability and efficiency.
• Contribute to monitoring and simulation systems to support software reliability and scalability.
• Identify and resolve performance bottlenecks related to infrastructure, memory usage, and runtime efficiency.
• Communicate technical concepts clearly to non‑technical stakeholders to align development with business goals.

Requirements

• Degree in Computer Science, Engineering, or equivalent experience
• Strong proficiency in Python and Linux environments; knowledge of Go or Rust is a plus.
• Proven experience developing and deploying scalable software systems, including production‑level code and real‑world performance optimization.
• Experience with cloud and big data technologies such as AWS, Spark, Airflow, and Kubernetes.
• Experience with CI/CD pipelines and automating software deployment processes (eg, GitHub Actions).
• Familiarity with optimization techniques, machine learning, and time‑series forecasting is highly valued.
• Excellent communication skills and the ability to collaborate within cross‑functional teams.
• Experience in energy solutions, battery control systems, and a passion for sustainability and clean energy solutions.
• Hands‑on experience with optimization techniques, time‑series forecasting, and ML model development focused on energy storage and grid applications is a plus.
• Experience managing containerized applications in embedded or firmware environments and optimizing resource usage (memory, CPU) for efficiency in constrained systems is a plus.

Technologies

• Python
• Linux
• Go
• Rust
• AWS
• Spark
• Airflow
• Kubernetes
• GitHub Actions

Benefits

• Medical plans with options requiring no payroll deduction
• Family-building, fertility, adoption and surrogacy benefits
• Dental (including orthodontic coverage) and vision plans with zero employee contributions
• Company‑paid HSA contributions when enrolled in a high‑deductible health plan
• Healthcare and Dependent Care Flexible Spending Accounts (FSA)
• 401(k) with employer match, Employee Stock Purchase Plan, and other financial benefits
• Company‑paid Basic Life and AD&D insurance
• Short‑term and long‑term disability insurance with a 90‑day waiting period
• Employee Assistance Program
• Sick leave, vacation time, and paid holidays (flex time for salary roles; accrued hours for hourly roles)
• 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

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. The role centers on advanced algorithms that determine the best times to store and use energy, accounting for electricity prices, solar generation, and grid conditions. These optimizations power Tesla’s energy products, including Megapacks, Powerwalls, Virtual Power Plants, and microgrids.

Expected Compensation

Salary range: $140,000 - $300,000 per year, plus cash and stock awards and benefits. The final offer may vary based on location, job‑related knowledge, skills, and experience, and may include additional elements described in an employment offer.