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Embodied AI / Simulation Engineer

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Formic

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Location:
United States , San Francisco ▼

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

145000.00 - 200000.00 USD / Year
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Job Description:

As an Embodied AI / Simulation Engineer, you will develop learning-based manipulation systems for humanoid and mobile manipulation platforms and ensure they transfer reliably into the real world. You will build the simulation, data, and training infrastructure needed to develop robust visuomotor policies and deploy them onto physical robotic systems operating in production environments. This role sits at the intersection of simulation, machine learning, and robotics execution. You will work closely with perception and controls teams to ensure learned policies operate safely, reliably, and effectively in closed-loop real-world conditions.

Job Responsibility:

  • Design and train learning-based manipulation systems for humanoid and mobile manipulation platforms
  • Develop and maintain high-fidelity digital twins using Isaac Sim, MuJoCo, or similar simulation tools
  • Implement and evaluate approaches including Action Chunking with Transformers (ACT), diffusion policies, behavior cloning, and Vision-Language-Action (VLA) models
  • Contribute to development of a Universal Manipulation Interface (UMI) abstraction layer
  • Build teleoperation-to-training data pipelines to enable scalable dataset generation
  • Design sim-to-real transfer strategies including domain randomization and system identification
  • Evaluate policy robustness, failure modes, and cross-task generalization
  • Partner with perception and controls teams to ensure stable closed-loop visuomotor policies
  • Deploy trained models onto real robotic systems and support on-hardware validation and debugging
  • Establish experimental rigor through structured evaluation, ablations, and performance tracking

Requirements:

  • Experience training embodied AI policies for real robotic systems
  • Strong understanding of sim-to-real challenges and real-world failure modes
  • Familiarity with transformer-based action models such as ACT
  • Experience with diffusion policies or other generative control approaches
  • Experience working with multi-modal inputs including vision, proprioception, and language
  • Proficiency in Python and deep learning frameworks such as PyTorch or JAX
  • Experience integrating learned policies with real-time control system
  • Strong experimental design, evaluation discipline, and attention to reproducibility
  • Ability to operate across research and deployment constraints without losing rigor
What we offer:
  • Equity in Formic
  • Competitive & Uncapped Commission Structure
  • Comprehensive Healthcare Coverage: Medical, dental, and vision insurance through Blue Cross Blue Shield and Unum, with 99% of employee premiums covered and 75% coverage for dependents
  • Additional Insurance Benefits: FSA and DCFSA, life insurance, short-term disability, and long-term disability through Unum, all 100% employer-paid
  • Employee Assistance Program (EAP)
  • Paid Parental Leave Program: Up to 12 weeks of paid parental leave
  • Company-sponsored 401(k)
  • Home Office Stipend: A one-time allowance for fully remote and hybrid employees
  • Monthly Cell Phone Reimbursement
  • Flexible Time Off

Additional Information:

Job Posted:
February 20, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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