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Machine Simulation Engineer Jobs (NOW HIRING)

Denso

Simulation Engineer 3

Southfield, MI · On-site

$107K - $133K/yr

We are seeking an experienced Simulation Engineer with manufacturing experience, specializing in ... Proficiency in using IoT, AI, and machine learning to support digital transformation in ...

Blue Origin LLC

Senior Simulation Engineer

Seattle, WA · On-site

$197K - $276K/yr

... machine learning training activities- Mature Isaac Sim + Newton models into verification-grade ... junior engineers and establish best practices for simulation/modeling software quality and ...

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Machine Simulation Engineer information

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How much do machine simulation engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine simulation engineer in the United States is $123,399.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,000.00 and $146,500.00 per year, depending on experience, location, and employer.

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Infographic showing various Machine Simulation Engineer job openings in the United States as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $123,399 per year, or $59.3 per hour.

Senior Simulation Engineer - W2 Role

Mountain View, CA • On-site

Saransh Inc
IT Services • 51 - 200 employees
Learn more about Saransh Incexternal

Contractor

Re-posted 2 days ago

Job description

Role: Senior Simulation Engineer
Location: Mountain View, CA (Hybrid Onsite)
Job Type: W2 Contract
 
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, 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.