Simulation Engineer

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Position:

Simulation Engineer

Location:

Mountainview CA Hybrid

Duration: 12+Months with possible extensions

Job Description:

We are seeking a highly skilled Senior Simulation Engineer to own and accelerate our synthetic data generation capabilities. This role is crucial for bridging the gap between our high-fidelity simulation environment and our production ML models. You will be responsible for architecting, implementing, and maintaining the entire simulation-to-data pipeline, ensuring a consistent and massive flow of quality training data.

Key Responsibilities:

Simulation Acceleration & Data Collection:Directly utilize expertise in NVIDIA Isaac Sim to design, script, and optimize simulation scenarios specifically tailored to generate high-quality, diverse data for VLA (Vision-Language Alignment) and NOVA model training objectives.

Pipeline Architecture:Design, build, and maintain robust, scalable pipelines for CAD ingestion, scene creation, sensor emulation, and data processing within the Isaac Sim framework.

Synthetic Data Management:Implement and manage advanced auto-annotation tools within the simulation environment to rapidly label complex sensory data (e.g., 3D bounding boxes, semantic segmentation, depth maps) for supervised learning.

Environment Maintenance:Take ownership of setting up, configuring, and maintaining the simulation environment (including hardware/software dependencies, GPU utilization, and headless operation) to ensure reliable, large-scale parallel execution.

Cross-Functional Support:Collaborate closely with the Machine Learning Engineering team to analyze data gaps, iterate on simulation parameters, and ensure the synthetic data distribution matches the necessary complexity and variability of real-world deployment.

Performance Tuning:

Profile and optimize simulation execution speed to maximize data throughput, essential for rapid iteration cycles in model tuning.

Required Qualifications:

Expertise in Simulation: 3+ years of hands-on experience with NVIDIA Isaac Sim (or a comparable high-fidelity physics simulator like Unity/Unreal used for robotics).

Programming Proficiency:

Expert-level proficiency in Python for scripting, automation, data pipeline construction, and tool development.

Robotics Fundamentals:

Strong understanding of robotics kinematics, sensor physics (LIDAR, RGB-D cameras, IMU), and their accurate representation in simulation.

ML Data Pipeline Experience:Proven experience setting up automated data collection pipelines for Deep Learning projects, including experience with data versioning and metadata management.

CAD/3D Workflow:

Familiarity with 3D assets, CAD formats, and procedural generation techniques to create complex virtual scenes.

Preferred Qualifications:

Familiarity with VLA/NOVA model architectures or similar foundation models in robotics.

Experience with cloud computing environments (AWS, Azure, Google Cloud Platform) for scaling simulation jobs.

Familiarity with other robotics simulation/middleware like ROS/ROS 2.

Experience with hardware-in-the-loop (HIL) or software-in-the-loop (SITL) testing methodologies.