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AI Sim-to-Real Transfer Engineer

Riley Magnusson

Full-time · Job · Los_Angeles

About the role

Training a robot to pick irregular objects in simulation takes 4 hours. Getting that policy to work on a real robot arm takes 4 months. The sim-to-real gap is the single biggest bottleneck in our product development cycle, and closing it is the most impactful engineering problem we have. We build autonomous manipulation systems for warehouse logistics — robot arms that pick, pack, and palletize 200+ SKU types without per-item programming. The physics sim produces training data at 1000x real-time speed, but domain randomization alone isn't enough to bridge the reality gap. We need someone who can combine domain randomization, system identification, progressive training curricula, and real-world fine-tuning into a repeatable transfer methodology. You'll work in our Palo Alto lab 3 days per week with access to 12 robot cells and a full sensor suite. The remaining 2 days are remote. The robotics team is 15 engineers; you'll own the sim-to-real pipeline end-to-end.

Responsibilities

  • Develop and refine sim-to-real transfer methodologies for manipulation policies
  • Design domain randomization strategies that improve transfer success rates
  • Build automated evaluation pipelines comparing sim and real performance
  • Run real-world experiments to validate and tune transferred policies
  • Collaborate with sim engineers to improve physics fidelity where it matters
  • Document transfer recipes for different task categories

Requirements

  • 5+ years in robotics or RL with hands-on sim-to-real experience
  • Deep expertise in reinforcement learning and policy optimization
  • Experience with physics simulators like MuJoCo, Isaac Gym, or PyBullet
  • Strong Python and PyTorch skills
  • Comfort working with physical robot hardware and sensor systems

Benefits

  • Hybrid role — 3 days lab, 2 days remote
  • Top-of-market compensation plus equity
  • Health, dental, vision, and life insurance
  • $5,000 annual conference and education budget
  • Relocation assistance available

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch reinforcement learning docker gcp

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Job Type

Full-time

Level

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Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch reinforcement learning docker gcp

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