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Open nowPosted yesterday

Robotics Simulation Engineer – Physical AI & Digital Twins

autostore28 open roles

Where
Atlanta, GA, USA
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Your applicationOpen nowRobotics Simulation Engineer – Physical AI & Digital Twinsautostore · Atlanta, GA, USA

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The clock on this job

Early applications get read.

11.3% of postings close within 7 days. Measured by our own scanner across the market. autostore postings stay open a median of 8 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.2%3 days
  3. 11.3%7 days
  4. 17.6%14 days
  5. 34.3%30 days
  6. 43.5%60 days
This job: posted yesterday

autostore median: 8 days open

The posting

AutoStore™ holds a simple yet powerful vision: to store and move things for everyone, everywhere. Founded in Norway, we've grown into a global technology company. AutoStore uses advanced software to automate and orchestrate order fulfillment. Our goal is to ensure orders arrive faster than ever, with minimal environmental impact. That’s how we help brands exceed customer expectations.

We have more than 1600 systems in nearly 60 countries, and we grow continuously as a community of employees, partners, customers, suppliers, and connected technologies. Automation should make life easier, and by listening carefully to our community, we innovate to meet the industry’s most complex needs. With AutoStore™, brands gain speed, efficiency, improved workplaces, and much more floor space.

AutoStore – moving things forward.

The Role:

As a Robotics Simulation Engineer at AutoStore, you will build the virtual environments where our robots, grids and Physical AI systems are tested before they are built. Your work lets teams test far more scenarios than physical prototypes allow and find failures before they reach the field.

You will join the New Product Development Innovation Team in Atlanta and work closely with the Engineering Tools and Services team. Day to day, you will work with mechanical, electrical, controls, software and AI engineers to turn their questions into simulations they can run themselves.

This is a great role for someone who enjoys working across disciplines, building tools other engineers love to use, and seeing virtual results become real products running in more than 1,600 systems worldwide.

Key Tasks and Responsibilities:

  • Develop and run physics-based simulation environments (e.g., NVIDIA Isaac Sim, Gazebo, MuJoCo) for end-to-end testing of robots and Physical AI products.
  • Build digital twins of AutoStore hardware and compare them with lab and field data to measure and improve fidelity.
  • Set up software-in-the-loop and hardware-in-the-loop test benches, and add simulation test cases to regression and CI pipelines.
  • Develop scenario generation and stress-testing methods to find unknown failure modes and edge cases.
  • With the Engineering Tools and Services team, build tools and automated workflows so engineers can run what-if analyses and parameter sweeps without being simulation experts.
  • Generate synthetic data and simulation environments to train and evaluate perception and AI models.
  • Work with each team to pick the right level of model detail for the question, and present results clearly.

Key Qualifications:

  • 3+ years of experience applying simulation in robotics, hardware engineering or product development. A senior-level position is available for well-qualified candidates.
  • Hands-on experience with physics-based robotics simulators such as NVIDIA Isaac Sim, Gazebo, MuJoCo, PyBullet or Webots.
  • Strong Python programming skills (C++ a plus), with experience automating simulation workflows and analyzing large result sets.
  • Solid grasp of rigid-body dynamics, kinematics, sensors and actuators.
  • Experience with automated testing, including software-in-the-loop, hardware-in-the-loop or simulation in CI/CD.
  • Personable and collaborative; able to explain results and their uncertainty to technical and non-technical audiences.
  • Bachelor's degree or higher in Mechanical, Electrical or Robotics Engineering, Computer Science, or a related field.

Preferred Qualifications:

  • Experience with photorealistic rendering and synthetic data generation (e.g., Isaac Sim Replicator, NVIDIA Omniverse, Unreal Engine, Blender) or reinforcement learning environments (e.g., Isaac Lab, Gymnasium).
  • Familiarity with system identification, parameter estimation, sensitivity analysis or uncertainty quantification.
  • Experience with traditional FEA tools (e.g., Ansys Mechanical, Abaqus) and 3D CAD (e.g., SolidWorks, Creo or NX).
  • Experience scaling simulations across GPUs, clusters or cloud.
  • Background in robotics, logistics automation or other electromechanical systems.

We Offer:

AutoStore believes in taking care of employees and is dedicated to providing a supportive and rewarding work environment. Join us in our mission to store and move things for everyone, everywhere.

  • Comprehensive Medical, Dental, and Vision plans
  • Health Savings Account (HSA) with a company contribution
  • Generous Paid Time Off including 12 holidays, paid exercise time, paid volunteer time, and paid parental leave plans for all new parents
  • Retirement 401(k) plan with employer match and discretionary profit sharing contribution
  • Educational assistance and professional development programs, including mentorship/coaching programs with external industry leaders
  • Additional benefits include Group Life Insurance, Voluntary Additional Life Insurance, Disability Insurance, Employee Assistance programs, and more!

AutoStore is an Equal Opportunity Employer that does not discriminate on the basis of actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth, pregnancy-related conditions, and lactation), gender identity or expression (including transgender status), sexual orientation, marital status, military service and veteran status, physical or mental disability, genetic information, or any other characteristic protected by applicable federal, state, or local laws and ordinances.

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