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Pipeline Simulation Jobs in California (NOW HIRING)

Apple

Simulation Engineer - Camera Hardware

Sunnyvale, CA · On-site

$150K - $277K/yr

You'll work directly with partner teams to build simulation pipelines that transform turnaround times from weeks to days, enabling self-service workflows that accelerate engineering across the ...

Apex

Simulation Engineer

Los Angeles, CA · On-site

$145K - $185K/yr

... pipelines, and agile development • Experience designing, implementing, and validating physics-based simulation models for closed-loop systems • Experience emulating and integrating virtual ...

1X

Software Engineer - Simulation

San Carlos, CA · On-site

... pipelines • Strong testing practices for simulation stacks used in robot learning--comfortable writing tests that verify physical correctness and catch regressions • Advanced degree (MS or PhD ...

DensityAI

Simulation Engineer

Mountain View, CA

Solid computer-architecture fundamentals - pipelines, memory hierarchy, ISAs, and accelerator/GPU-class datapaths - enough to model hardware faithfully * Real simulation/modeling judgment: functional ...

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Pipeline Simulation information

What is the difference between Pipeline Simulation vs Pipeline Engineer?

AspectPipeline SimulationPipeline Engineer
Primary FocusModeling and analyzing pipeline systems using simulation softwareDesign, construction, and maintenance of pipeline infrastructure
Required CredentialsEngineering degree, knowledge of simulation toolsEngineering degree, often professional engineering license
Work EnvironmentSoftware labs, office settings, project planningField sites, construction sites, office work
Industry UsageUsed for planning, safety analysis, and optimizationInvolved in actual pipeline development and operations

Pipeline Simulation specialists focus on modeling pipeline systems to optimize performance and ensure safety, often working in software environments. Pipeline Engineers are responsible for designing and maintaining pipeline infrastructure in the field. Both roles require engineering backgrounds, but their daily tasks and work environments differ significantly.

What are popular job titles related to Pipeline Simulation jobs in California? For Pipeline Simulation jobs in California, the most frequently searched job titles are:
What job categories do people searching Pipeline Simulation jobs in California look for? The top searched job categories for Pipeline Simulation jobs in California are:
What cities in California are hiring for Pipeline Simulation jobs? Cities in California with the most Pipeline Simulation job openings:
Pipeline Simulation jobs near you
Infographic showing various Pipeline Simulation job openings in California as of July 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution.

Senior Simulation Engineer - W2 Role

Saransh Inc

Mountain View, CA • On-site

Contractor

Re-posted 22 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.