Staff Data Scientist – Simulation Motion AI

SLAS (Society for Laboratory Automation and Screening); Peachtree Corners (GA); On-site; USD 150,000 - 230,000; Full time

Job summary

Intuitive is seeking a Staff Data Scientist – Simulation Motion AI to design scalable simulation-data systems for training robotic policies. You will collaborate with policy teams, test, regulatory, product, and clinical units to generate data and evaluate algorithms at scale in simulation for motion AI products.

Requirements include a PhD/Master’s in a technical field and 9+ years (or 4+ with PhD) with Python, PyTorch, and robotics simulation platforms, plus experience in prosthetic motion,

Qualifications

• PhD or Master’s degree in CS, robotics, ML, data science, EE or related field.
• 9+ years in industry building simulation, ML, robotics, CV, or autonomous-systems software; or 4+ years with a PhD.
• Experience with major robotics simulation platforms (NVIDIA Isaac Sim/Lab, MuJoCo).
• Proficiency in Python and PyTorch; robotics kinematics and control basics.

Responsibilities

• Architect scalable synthetic data pipelines for training robotic policies in simulation.
• Develop and test simulation environments and curricula for long-horizon tasks.
• Create provenance, metadata, versioning, and reproducibility standards for datasets.
• Collaborate with cross-functional teams including product, clinical, and regulatory groups.

Skills

Python

PyTorch

Robotics

Simulation

Machine learning

Data pipelines

Kinematics

Education

PhD or Master’s degree in CS/Robotics/ML

Tools

NVIDIA Isaac Sim

MuJoCo

Job description

Company Description

It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care, our technologies - like the da Vinci surgical system and Ion - have transformed how care is delivered for millions of patients worldwide.

We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.

The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful - because every improvement we make has the potential to change a life.

If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare, you’ll find your purpose here.

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, MuJoCo, 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.

Qualifications

Required Qualifications

• PhD or Master’s degree in Computer Science, robotics, machine learning, data science, electrical engineering, mechanical engineering, applied mathematics, or a related technical field.
• 9+ years of industry experience, post training, developing simulation, machine learning, robotics, computer vision, simulation, or autonomous-systems software; or 4+ years of industry experience with a PhD
• Proven hands-on experience with at least one major robotics simulation platform: NVIDIA Isaac Sim, NVIDIA Isaac Lab, MuJoCo or Equivalent physics-based robotics simulation environment
• Expertise in creating custom simulation environments, robot assets, task definitions, sensors, reward functions, termination criteria, or procedural scene-generation systems.
• Expertise with Python and modern machine-learning frameworks such as PyTorch
• Experience working with robot kinematics, dynamics, coordinate frames, calibration, trajectory representations, and closed-loop control and designing datasets and experiments for multimodal or time-series machine learning.
• Demonstrated ability to diagnose model failures using quantitative analysis rather than relying solely on aggregate success metrics.
• Experience deploying, testing, or validating models on physical robotic systems.

Preferred Qualifications

• Experience developing vision-based manipulation policies using RGB, stereo, depth, segmentation, optical flow, keypoints, or learned visual representations.
• Experience with transformer, diffusion, or vision-language-action for robotics.
• Experience with deformable-object simulation, articulated objects, fluids, cables, sutures, tissue, or other contact-rich environments.
• Experience with experiment tracking, dataset versioning, distributed training, and large-scale simulation infrastructure.
• Familiarity with containerized and distributed computing technologies such as Docker, Kubernetes, Slurm, Ray, or cloud GPU platforms.
• Experience in a safety-critical field such as medical robotics, autonomous vehicles, aviation, industrial automation, or defense.
• Proficiency in GPU optimization for either inference or rendering

Additional Information

Due to the nature of our business and the role, please note that Intuitive and/or your customer(s) may require that you show current proof of vaccination against certain diseases including COVID-19. Details can vary by role.

Intuitive is an Equal Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws.

Mandatory Notices

U.S. Export Controls Disclaimer: In accordance with the U.S. Export Administration Regulations (15 CFR 743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employeeswho are nationals from countries currently on embargo or sanctions status.

We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws.

Preference will be given to qualified candidates who do not reside, or plan to reside, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississippi, Missouri, Oklahoma, Pennsylvania, South Carolina, or Tennessee.

This position may be filled at a different job level than listed here depending on

business need and/or on the selected candidate’s experience, knowledge and skills.

Compensation will be based primarily on the job level at which the role is filled and the

Candidate’s Qualifications, Consistent With Applicable Law.

We provide market-competitive compensation packages, inclusive of base pay, incentives, benefits, and equity. It would not be typical for someone to be hired at the top end of range for the role, as actual pay will be determined based on several factors, including experience, skills, and qualifications. The target compensation ranges are listed.