Tesla

Makes electric cars, robotaxis and grid batteries

Senior Machine Learning Engineer - Pricing, Robotaxi

Applied Machine LearningConfirmed live in the last 24 hours

Full-timePalo Alto, CA, USANo salary listedIn-person

About the Job

Requirements

A degree in Computer Science, Machine Learning, Operations Research, Economics, or a related field; proof of exceptional skills in a related field or equivalent experience is also accepted.
At least 4 years of experience developing and deploying machine learning models and pricing or marketplace algorithms in large-scale production environments.
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 and deep learning or machine learning/reinforcement learning for pricing and real-time decisioning.
Ability to solve open-ended, difficult technical problems with little guidance.
Ability to collaborate across product, finance, billing, and engineering.

Responsibilities

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 machine learning and optimization pipelines, including 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 fleet scaling can be maintained economically.

Desired Qualifications

Experience in rideshare, marketplace, or large-scale dynamic pricing.

Category	Engineering & Information Technology
Location	Palo Alto, California
Requisition ID	284175
Type	Full-time

Job Description

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.

Job Responsibilities

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

Job Requirements

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

About the Company

Tesla

Makes electric cars, robotaxis and grid batteries

Tesla makes electric cars and batteries that store power for homes and utilities, and it develops self-driving software and humanoid robots. In 2023, its Model Y became the first electric vehicle to rank as the world's best-selling car. Buyers order the Model 3 sedan, Model Y SUV, or Cybertruck pickup directly from Tesla instead of through dealers, and they charge on its Supercharger fast-charging network. It also sells Megapack and Powerwall batteries, runs a robotaxi service, and charges drivers a monthly fee for self-driving software that still needs their supervision. Tesla was founded in 2003, with Elon Musk as its lead early investor and a recognized co-founder, and it is based in Austin, Texas.

Company size: 10,001+
Company stage: IPO
Headquarters: Austin, TX
Founded: 2003

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