Tesla
AI

Machine Learning Engineer

Tesla · Fremont, CA, US · $140k - $210k

Actively hiring Posted about 1 month ago

Role overview

What to Expect

We are looking for a highly skilled and motivated Machine Learning Engineer to support and upscale our Service Supply Chain Distribution strategies. You will be part of the Supply Chain Optimization team that is managing strategic projects and continuous improvement efforts for Tesla’s Global Distribution Network. The role requires the ability to build strong cross-functional working relationships with Material Planning, Logistics, Finance, Warehouse Operations and Service Operations teams. You will require a sharp business focus, a collaborative style of working, and a proactive and critical mindset. You need to acquire deep subject matter knowledge about systems, sourcing, planning and fulfillment processes to build models that drive impactful business changes. It is essential that you can think strategically, connect the dots in the bigger picture, as well as be comfortable in the details of the deliverables to drive operational improvements. The role is expected to simultaneously handle multiple projects of department-level scale and global reach.

What You'll Do

  • Build and productionize ML models & AI agents that power inbound network design, including cost, transit-time prediction, mode/route selection, and consolidation strategies
  • Design and extend our Digital Twin, integrating inbound network constraints to mirror real-world designs and enable near real-time decision support
  • Build and run large-scale “what-if” simulations to evaluate new inbound strategies quantifying the impact on cost, service levels, and DC operations
  • Perform sensitivity and stress testing on existing inbound network designs to identify bottlenecks, failure modes, and resiliency gaps, and translate findings into concrete recommendations for improvements
  • Own the ML lifecycle for inbound use cases: data pipelines, feature engineering, model evaluation, AB-testing, monitoring, and continuous retraining based on realized performance versus modeled expectations
  • Collaborate closely with Material Planning, Logistics, Finance, and Warehouse Operations to turn analytical outputs into executable inbound pilots and long-term standards, tracking realized performance vs. modeled expectations
  • Build decision-support tools, APIs, and UIs that expose inbound simulations, recommendations, and KPIs directly in our internal Digital Twin, enabling self-serve analysis for cross-functional partners
  • Translate complex quantitative results into clear narratives and visualizations, enabling leadership to make informed tradeoffs between cost, service, and operational complexity in the inbound network

What You'll Bring

  • Degree in computer science, AI, Applied Math, Operations Research, or related field, or equivalent experience
  • Strong Mathematical fundamentals and algorithms skills
  • Excellent programming, debugging, performance analysis, and test design skills
  • Strong programming skills in SQL, Python (experience with libraries such as NumPy, pandas, scikit-learn, TensorFlow, or PyTorch)
  • Hands-on experience developing full-stack applications using Django (Python), Java-based services, and react, with a strong understanding of RESTful API design and integration
  • Knowledge of MLOps practices, including CI/CD pipelines, model monitoring, and experience with containerization and orchestration tools such as Docker and Kubernetes
  • Experience leveraging LLMs, multimodal unsupervised learning, and Generative AI to drive innovative supply chain optimization solutions

Compensation and Benefits

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 - $210,000/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.

Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws.

Tesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process.

What you'll work on

  • Degree in computer science, AI, Applied Math, Operations Research, or related field, or equivalent experience
  • Strong Mathematical fundamentals and algorithms skills
  • Excellent programming, debugging, performance analysis, and test design skills
  • Strong programming skills in SQL, Python (experience with libraries such as NumPy, pandas, scikit-learn, TensorFlow, or PyTorch)
  • Hands-on experience developing full-stack applications using Django (Python), Java-based services, and react, with a strong understanding of RESTful API design and integration
  • Knowledge of MLOps practices, including CI/CD pipelines, model monitoring, and experience with containerization and orchestration tools such as Docker and Kubernetes
  • Experience leveraging LLMs, multimodal unsupervised learning, and Generative AI to drive innovative supply chain optimization solutions

Tags & focus areas

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Fulltime Machine Learning Generative Ai Ai