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Simulation Engineer

Job in Milpitas, Santa Clara County, California, 95035, USA
Listing for: UnitX
Full Time position
Listed on 2026-07-03
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 100000 - 130000 USD Yearly USD 100000.00 130000.00 YEAR
Job Description & How to Apply Below

Title

Simulation Engineer

About Us

UnitX builds the world's leading physical AI systems to automate repetitive visual tasks in factories. UnitX is a fast-moving startup with a team from Stanford, MIT, Google, and beyond. Since inception, UnitX has deployed 1,000+ mission‑critical systems across 190+ of the world's leading manufacturers' production lines. Every year, $15B worth of products go through UnitX's AI inspection system to ensure quality.

Role Overview

We are seeking a highly skilled Simulation Engineer to design and build high‑fidelity, scalable simulation platforms. In this role, you will architect modular simulation environments that accurately mirror real‑world physical interactions and sensor outputs, enabling the robust training, testing, and validation of advanced AI‑driven systems. You will play a critical part in closing the sim‑to‑real gap, ensuring that our simulated environments produce reliable, predictable, and reproducible outcomes in the physical world.

Key Responsibilities
  • Platform Architecture: Design, develop, and maintain a modular, extensible, and customizable simulation platform tailored for scalable AI applications.

  • Physics & Dynamics Modeling: Leverage state‑of‑the‑art simulation and physics engines to accurately model realistic physical interactions, including rigid body dynamics, complex geometries, and diverse material properties.

  • Sensor Simulation & Calibration: Develop and calibrate high‑fidelity simulation models for diverse sensor modalities. Establish rigorous, quantitative validation metrics to ensure simulated perception accurately matches real‑world ground truth.

  • ML & Synthetic Data Pipelines: Architect scalable pipelines for high‑throughput offline synthetic data generation, ensuring seamless integration with machine learning training loops (e.g., Reinforcement Learning, Computer Vision).

  • Sim-to‑Real Optimization: Proactively identify and mitigate risks, failure modes, and bottlenecks for synthetic data generation pipeline. Define and monitor metrics to continually measure and minimize the sim‑to‑real gap.

  • Hardware & Environment Modularization: Implement highly configurable asset pipelines to support a wide variety of hardware topologies, sensor configurations, and dynamic operational layouts.

  • Scaling Future Simulation Diversity: Architect foundational systems capable of supporting next‑generation, contact‑rich interactions. You will lay the groundwork for our future efforts in advanced domain randomization—expanding spatial, visual, and physical parameters as our AI models scale in complexity over time.

Basic Qualifications
  • Education & Experience: Bachelor's degree in Computer Science, Robotics, Engineering, or a related field with 4+ years of professional experience; OR a Master's degree/Ph.D. with 2+ years of relevant experience.

  • Industry Track Record: Proven experience contributing to the successful release of a customer‑facing product or complex system that heavily relies on simulation (e.g., robotic digital twins, autonomous vehicles, UAV systems, or AAA video games).

  • Technical Proficiency: Strong software engineering fundamentals with deep expertise in C++ or Python
    .

  • Simulation Ecosystems: Hands‑on experience with modern simulation frameworks (e.g., NVIDIA Isaac Sim, Drake, Mu Jo Co ) or industry‑standard 3D game engines (e.g., Unreal Engine, Unity).

Preferred Qualifications
  • 3D Asset Tool chains: Proficiency with industry‑standard 3D asset and robotics description formats (e.g., USD, URDF, MJCF, glTF) and experience building automated CAD‑to‑sim pipelines.

  • Machine Learning Integration: Hands‑on experience interfacing simulators with modern ML frameworks (e.g., PyTorch, Tensor Flow) for synthetic data generation or autonomous agent training.

  • Advanced Sensor Fidelity: Proven track record of tuning, calibrating, and validating complex simulated sensor suites (e.g., optical, depth, spatial, or tactile sensors) against physical counterparts.

  • Distributed Computing: Familiarity with cloud platforms (AWS, GCP) and containerization (Docker, Kubernetes) for parallelizing and scaling massive simulation workloads.

Benefits
  • Competitive salary & equity

  • Unlimited PTO

  • Full Medical, Dental, Vision, 401k

  • Daily meals provided with your own choice

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