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Simulation Engineer

Job in Milpitas, Santa Clara County, California, 95035, USA
Listing for: UnitX
Full Time position
Listed on 2026-05-13
Job specializations:
  • Engineering
    Systems Engineer, Robotics, AI Engineer, Software Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Overview

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.

Title: Senior Simulation Engineer

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.

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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