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Robotics Simulation Jobs in Georgia (NOW HIRING)

CA$140K/yr

Bachelor's in Computer Science, Electrical Engineering, Robotics, or related field * Strong Python, with a track record of maintainable code in a shared codebase * Hands-on simulation experience for ...

At Slip Robotics, we are at the forefront of revolutionizing the logistics and automation industry ... Perform detailed analysis and simulations to validate and optimize electrical designs, considering ...

At Slip Robotics, we are at the forefront of revolutionizing the logistics and automation industry ... Perform detailed analysis and simulations to validate and optimize electrical designs, considering ...

Introduction Slip Robotics is a pioneering Series B startup transforming the logistics and freight ... Expertise in CAD (e.g., SolidWorks, Onshape, PDM), FEA/simulation, tolerance analysis, and DFM/DFA ...

Introduction Slip Robotics is a pioneering Series B startup transforming the logistics and freight ... Expertise in CAD (e.g., SolidWorks, Onshape, PDM), FEA/simulation, tolerance analysis, and DFM/DFA ...

Introduction Slip Robotics is a pioneering Series B startup transforming the logistics and freight ... Expertise in CAD (e.g., SolidWorks, Onshape, PDM), FEA/simulation, tolerance analysis, and DFM/DFA ...

Showing results 21-40

Robotics Simulation information

What is robotics simulation?

Robotics simulation is the use of computer software to model and test the behavior of robots in a virtual environment. This allows engineers and researchers to design, program, and optimize robots without needing physical prototypes, saving time and resources. Simulations can replicate real-world conditions, enabling the analysis of robot movement, sensor data, and task performance before implementation. Robotics simulation is commonly used in developing autonomous systems, industrial automation, and research applications.

What are the key skills and qualifications needed to thrive as a robotics simulation engineer?

To thrive as a Robotics Simulation Engineer, you need a strong background in robotics, computer science, and mathematics, often supported by a relevant degree such as electrical engineering or mechanical engineering. Familiarity with simulation tools like Gazebo, ROS (Robot Operating System), MATLAB/Simulink, and programming languages such as Python or C++ is essential. Problem-solving, attention to detail, and effective teamwork are key soft skills that help in designing and refining complex simulation models. These abilities are crucial for creating accurate simulations that accelerate development, testing, and deployment of robotic systems.

What are some typical challenges faced when working in robotics simulation, and how can they be addressed?

Professionals in robotics simulation often encounter challenges such as accurately modeling real-world physics, ensuring simulation fidelity, and integrating with hardware or software systems. Addressing these requires a strong understanding of both robotics and simulation tools, as well as effective collaboration with engineers, software developers, and testers. Staying updated with advancements in simulation platforms and maintaining clear documentation are key strategies to overcome these challenges and ensure the simulations provide meaningful insights for development and testing.

What is the difference between Robotics Simulation vs Robotics Software Engineer?

AspectRobotics SimulationRobotics Software Engineer
Required CredentialsBachelor's in Robotics, Computer Science, or related; experience with simulation toolsBachelor's or higher in Computer Science, Robotics, or related; programming skills
Work EnvironmentResearch labs, simulation platforms, development teamsSoftware development teams, robotics companies, tech firms
Industry UsageTesting algorithms, virtual prototyping, system validationDeveloping robot control software, algorithms, and integration
Common Search/ComparisonYesYes

Robotics Simulation focuses on creating virtual environments to test and validate robotic systems, while Robotics Software Engineers develop the actual software that controls robots. Both roles often collaborate but serve different stages of robotics development, with simulation emphasizing testing and validation, and software engineering focusing on implementation and coding.

What cities in Georgia are hiring for Robotics Simulation jobs?

Cities in Georgia with the most Robotics Simulation job openings:

Infographic showing various Robotics Simulation job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 13% Part Time, 7% Contract, and 3% Nights. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

Senior Software Engineer, Simulation

AeroVect Technologies Inc.

Atlanta, GA • On-site

$120 - $160/hr

Other

Posted 11 days ago


Job description

Who We Are

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.

You will own and extend the simulation tooling. A significant part of the role is test quality. A test suite that produces flaky failures does not provide usable information. Determinism, reproducibility, and verifying that each gate is capable of failing are ongoing responsibilities rather than one-off tasks.

You Will
  • Build and extend the capabilities of the simulation environment: integration with the production autonomy stack, the interfaces it consumes, vehicle and actor models, and the range of environmental and operational conditions that can be represented

  • Maintain and improve that integration as the autonomy stack evolves, including fidelity work where the difference between simulated and real inputs changes how the stack behaves

  • Build and operate scenario execution in the cloud: orchestration, parallelism, result aggregation, artifact capture, and runtime cost modelling

  • Build and extend the evaluation layer that turns a run into a verdict — assertions and pass/fail criteria precise enough to gate a release and stable enough to avoid false failures

  • Build failure-triage tooling: failure clustering, per-failure recordings, and dashboards that autonomy engineers can use without assistance

  • Extend the scenario authoring tooling used by the V&V team, across backend and frontend

  • Maintain simulation foundations: determinism and reproducibility, pipeline performance, and extending coverage to additional maps and sites

You Have
  • Bachelor’s in Computer Science, Electrical Engineering, Robotics, or related field

  • Strong Python, with a track record of maintainable code in a shared codebase

  • Hands-on simulation experience for autonomous systems, familiarity with simulation platforms such as CARLA, Applied Intuition, Foretellix, NVIDIA Omniverse, IsaacSim, Gazebo, or a proprietary in-house simulatorWorking knowledge of simulation, modelling, and validation methodology, including how simulated results are used to support claims about real-world behaviour

  • Docker and Linux, distributed-systems fundamentals, and experience with GPU-based simulation environmentsCI/CD and cloud execution, experience integrating automated test workflows into CI for end-to-end validation coverage

  • Experience analyzing simulation output and telemetry to identify performance bottlenecks and failure modes

  • Debugging and profiling skills suited to distributed, GPU-bound systems

We Prefer
  • Master’s in Computer Science, Robotics, or related field

  • Experience designing and validating safety-critical systems in autonomous driving, aerospace, or robotics

  • Experience developing or maintaining autonomous vehicle software stacks (ROS/ROS2)

  • Cloud-based simulation infrastructure and large-scale distributed test execution

  • Sensor modelling (camera, lidar, radar), environment generation, or perception ground-truth pipelines

  • Automated testing, continuous integration, and data-driven validation

  • Log/bag re-simulation from recorded real-world data

  • Test-signal quality work: flake reduction, determinism debugging, golden-output comparison

  • Safety standards exposure: ISO 26262, ISO 21448 (SOTIF), UL4600, ISO 13849

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