Sr. Machine Learning Engineer, Pricing, Robotaxi

What to Expect

The Future is Autonomous. Join the Robotaxi division and drive the autonomous revolution, unlocking democratized, safe, low-cost transportation for all. Your role, positioned at the center of many critical teams at Tesla, will be critical to the successful deployment of Robotaxi.

As Sr. ML Engineer for Pricing, using first principles, develop pricing algorithms that optimize for customer experience as well as operational revenue and costs. Price is the control surface of the network: it balances demand, utilization, wait time, and willingness to pay. You will design, train, and ship pricing algorithms that align rides with riders at price points that are sensible and extremely accessible. While also being competitive in every city, and economically rational for a driverless fleet.

You will go far beyond simple surge. Involving Route-based prices and session-based prices as well as elasticity that learns from every trip. The output of your work will be highly visible and impactful on the success of Robotaxi. We are on a path to transform mobility, and you work will unlock scaling and ride accessibility at unprecedented levels.

What You’ll Do

• Design, train, and productionize machine learning models for real-time Robotaxi pricing, including base fare, distance and time, demand, traffic, tolls, taxes, government fees, and location-specific surcharges

• Build price-elasticity, conversion, and competitive-response models

• Develop dynamic and contextual pricing, with logical guardrails that protect rider trust and quote fairness

• Productionize ML and optimization pipelines: feature engineering, training, low-latency inference, experimentation, monitoring, and rollback

• Analyze ride sessions, costs, and competitor prices to continuously improve the pricing stack. Assist global expansion with market-specific fees, airport, and event experiences

• Partner with growth and profitability teams to ensure scaling of our fleet can be maintained economically

What You’ll Bring

• Degree in Computer Science, Machine Learning, Operations Research, Economics, or a related field, proof of exceptional skills in a related field, or equivalent experience

• 4+ years developing and deploying machine learning models and pricing or marketplace algorithms in large-scale production environments

• Experience in rideshare, marketplace, or large-scale dynamic pricing strongly preferred

• Proficiency in Python and at least one of Go, C++, Java, or Scala. Experience building backend distributed systems and low-latency, user-facing services

• Experience with deep learning, causal machine learning, and/or reinforcement learning for pricing or real-time decisioning

• Experience with large-scale data systems, deep learning, ML/RL for pricing and real-time decisioning

• Strong experimentation instincts, first-principles economics, and high standards for optimal outcomes

• Ability to solve open-ended, difficult technical problems with little guidance. Excellent collaboration across product, finance, billing, and engineering