AI Engineer, Multimodal Pretraining, Autonomy & Robotics

  • Palo Alto, CA
  • Posted 1 day ago | Updated 1 hour ago

Overview

On Site
USD 140,000.00 per year
Full Time

Skills

Mathematics
Social Sciences
Reasoning
Audiovisual
Art
Robotics
Training
Artificial Intelligence
Python
Software Engineering
Optimization
Neural Network
Deep Learning
PyTorch
TensorFlow
JAX
Distributed Computing
Parallel Computing
Cross-functional Team
Problem Solving
Conflict Resolution
PPO
Payroll
Health Care
FSA
Finance
Apache Flex
Legal
Insurance

Job Details

Scaling transformers, as well as more recent advances in Reinforcement Learning with Verifiable Rewards (RLVR), has created models with Ph-D level intelligence in a wide variety of subject areas - from Math to Social Sciences. Yet these models continue to struggle in real-world physical reasoning, often struggling to tell left from right.
At Tesla AI, we want to develop Olympiad-level physical intelligence that will enable highly capable robots, both wheeled and legged. These models should be able to anticipate and reason about future movements of any object or scene at the level of a race car driver or professional athlete. To accomplish this, you will have access to petabytes of multimodal (video, audio, action etc.) real-world data from our global fleet of cars and robots, as well as Tesla's state-of-the-art compute resources.
In this role, you will have the opportunity to work on the datasets, infra, model architecture, eval and scaling laws necessary to pretrain a large multimodal model with an emphasis on real-world physical intelligence.

Responsibilities
  • Create multimodal pretraining datasets that utilize Tesla's fleet of robots
  • Develop training infra necessary to train large multimodal models
  • Invent new architectures for encoding and decoding multimodal inputs and outputs
  • Develop downstream evaluations that can guide the tuning of these large models
  • Run scaling laws for model size, dataset composition etc

Requirements
  • Proven experience in scaling and optimizing large AI models, with a strong understanding of infrastructure challenges and solutions
  • Proficiency in Python and a deep understanding of software engineering best practices
  • In-depth knowledge of deep learning fundamentals, including optimization techniques, loss functions, and neural network architectures
  • Experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX
  • Strong expertise in distributed computing and parallel processing techniques
  • Demonstrated ability to work collaboratively in a cross-functional team environment
  • Strong problem-solving skills and the ability to troubleshoot complex system-level issues

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:
  • Aetna PPO and HSA plans > 2 medical 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 Account) HSA Contribution when enrolled in the High Deductible Aetna 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
  • Employee Assistance Program
  • Sick and Vacation time (Flex time for salary 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 - $420,000/annual salary + cash and stock awards + benefitsPay 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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