Senior Simulation Engineer - W2

Role:
Senior Simulation Engineer

Location:
Mountain View, CA (Hybrid Onsite)

Job Type: W2 Contract

• 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.

• 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.

• 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.

• Familiarity with VLA/NOVA model architectures or similar foundation models in robotics.
• Experience with cloud computing environments (AWS, Azure, GCP) 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.