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Data Scientist – Simulation Motion AI

Job in Peachtree Corners, Gwinnett County, Georgia, 30092, USA
Listing for: Intuitive
Full Time position
Listed on 2026-09-11
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Robotics, Data Scientist
Salary/Wage Range or Industry Benchmark: 140000 - 210000 USD Yearly USD 140000.00 210000.00 YEAR
Job Description & How to Apply Below
Position: Staff Data Scientist – Simulation Motion AI

Job Description

Primary Function of Position

As a Staff Data Scientist - Simulation Motion AI, you will lead the design of scalable simulation-data systems used to train, evaluate, and improve robotic policies for complex, safety-critical motion AI products. You will work alongside foundation and policy model teams, test, regulatory, product and clinical teams to generate data, train and test algorithms in simulation at scale for motion AI products.

Responsibilities

  • Architect scalable pipelines for generating synthetic and procedurally varied robotic interaction data using Isaac Sim, Isaac Lab, Mu Jo Co , or similar simulators.

  • Build SOTA, scalable simulation environments developing task data generation, ML, and scene domain randomization strategies covering:

    • Robot initial conditions and calibration errors

    • Camera poses, optics, lighting, and occlusions

    • Object geometry, appearance, pose, and material properties

    • Contact, friction, compliance, deformation, and force variation

    • Tool wear, latency, noise, and actuator uncertainty

    • Nominal, edge-case, failure, and recovery conditions

  • Define data-generation curricula that progress from constrained primitive actions to long-horizon, multi-stage robotic tasks.

  • Generate targeted recovery data for rare but safety-relevant conditions, including failed grasps, object displacement, camera obstruction, tracking loss, unexpected contact, and partial task completion.

  • Design systems for efficiently replaying, perturbing, relabeling, and extending real-world robot trajectories in simulation.

  • Establish provenance, metadata, versioning, and reproducibility standards for simulated datasets.

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