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Carla Simulation Jobs (NOW HIRING)

AeroVect Technologies Inc.

NY · On-site

$120 - $160/hr

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 ...

Jobtailor

Senior Digital Twin Engineer

California, MO · On-site

$110 - $160/hr

Work hands-on with multiple digital-twin platforms, such as NVIDIA Omniverse, CARLA, Siemens NX/Teamcenter/Plant Simulation, Dassault 3DEXPERIENCE, Ansys Twin Builder, or similar, Unity or Unreal ...

Pronto

Robotics Test Engineer

San Francisco, CA · On-site

... simulation environments (Gazebo, CARLA, Isaac Sim, or proprietary) • Familiarity with pub/sub messaging systems (ZMQ, ROS, DDS) and binary serialization formats (Cap'n Proto, Protobuf) • C ...

Pronto

Robotics Test Engineer

San Francisco, CA · On-site

... simulation environments (Gazebo, CARLA, Isaac Sim, or proprietary) • Familiarity with pub/sub messaging systems (ZMQ, ROS, DDS) and binary serialization formats (Cap'n Proto, Protobuf) • C ...

Graphcore

Staff Digital Twin Engineer

Austin, TX · On-site

NVIDIA Omniverse (primary environment), CARLA, Siemens NX/Teamcenter/Plant Simulation, Dassault 3DEXPERIENCE, Ansys Twin Builder, Unity or similar. * Integrate engineering and operational data from ...

Graphcore

Staff Digital Twin Engineer

Austin, TX · On-site

NVIDIA Omniverse (primary environment), CARLA, Siemens NX/Teamcenter/Plant Simulation, Dassault 3DEXPERIENCE, Ansys Twin Builder, Unity or similar. * Integrate engineering and operational data from ...

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All JobsCarla Simulation Jobs

Carla Simulation information

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$11K

$67.6K

$121.5K

How much do carla simulation jobs pay per year?

As of Aug 15, 2026, the average yearly pay for carla simulation in the United States is $67,601.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,000.00 and $79,500.00 per year, depending on experience, location, and employer.

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

To thrive as a CARLA Simulation Engineer, you need strong programming skills (especially in Python and C++), experience with robotics or autonomous vehicle technologies, and a solid foundation in computer science or engineering. Familiarity with CARLA Simulator, ROS, Unreal Engine, and relevant machine learning frameworks is typically required. Excellent problem-solving, teamwork, and communication skills help you effectively collaborate and troubleshoot complex simulation scenarios. These abilities are crucial for developing, testing, and validating autonomous vehicle systems in realistic virtual environments.

What are some common challenges faced by engineers working with Carla simulation, and how can they be addressed?

Engineers working with Carla Simulation often face challenges such as managing complex sensor configurations, ensuring realistic scenario creation, and optimizing performance for large-scale simulations. Addressing these challenges typically involves staying current with Carla's updates, leveraging the active open-source community for support, and utilizing Carla's extensive documentation and APIs for customization. Collaborating closely with team members in data science, robotics, and software engineering also helps in troubleshooting technical issues and sharing best practices for simulation accuracy and efficiency.

What is Carla simulation?

Carla Simulation is an open-source simulator designed for the development, training, and validation of autonomous driving systems. It provides a highly realistic urban environment where users can test self-driving algorithms in various traffic scenarios and weather conditions without any real-world risk. Carla supports flexible sensor configurations, customizable maps, and detailed vehicle dynamics, making it a popular tool for researchers and engineers working in autonomous vehicles and robotics. The platform is widely used in academia and industry for safe and efficient autonomous driving research.

What is the difference between Carla Simulation vs Robot Simulation Engineer?

AspectCarla SimulationRobot Simulation Engineer
Required CredentialsKnowledge of autonomous vehicle simulation, programming skills in Python/C++, experience with Carla platformBackground in robotics, control systems, programming in C++/Python, experience with simulation tools
Work EnvironmentPrimarily software development, simulation testing, virtual environmentsRobotics labs, virtual and physical robot testing environments
Industry UsageAutonomous vehicle development, AI testing, simulation platformsRobotics, automation, research and development

Carla Simulation focuses on developing and utilizing simulation environments for autonomous vehicles, mainly in software. Robot Simulation Engineers work on simulating robotic systems across various industries, including manufacturing and research. While both roles involve simulation and programming, Carla Simulation is specialized in vehicle environments, whereas Robot Simulation Engineers have a broader scope in robotics applications.

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Carla Simulation jobs near you
Infographic showing various Carla Simulation job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $67,601 per year, or $32.5 per hour.

Senior Software Engineer, Simulation

AeroVect Technologies Inc.

NY • On-site

$120 - $160/hr

Other

Posted 5 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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