Job description

Simulation Computer Vision or ML Engineer Location: Sunnyvale, CA — Hybrid, 3 days onsite per week Compensation: $95 - $100/hr on W2 Contract Duration: 12 Months with potential extension About the Role We are looking for a Simulation CV/ML Engineer to help build and operate camera and sensor simulation pipelines that enable next-generation computer vision and machine learning development. In this role, you will work at the intersection of camera simulation, synthetic data generation, ML infrastructure, and computer vision . You will generate high-quality synthetic datasets on demand, configure simulated camera and sensor environments, support ML training and evaluation workflows, and use model performance insights to continuously improve dataset composition. The ideal candidate combines strong Python and C++ software engineering skills with practical knowledge of camera systems, sensor modeling, image formation, and ML training pipelines . You will collaborate closely with camera architects, ML engineers, and perception teams to deliver reliable simulation data under demanding timelines. Job Responsibilities • Run, maintain, and iterate on camera and sensor simulation pipelines to generate synthetic datasets on demand. • Configure simulation scenes, camera parameters, and sensor models based on customer and camera architect specifications. • Deliver high-quality training and evaluation datasets to camera architecture, ML, and perception teams within tight development timelines. • Support ML model training and evaluation workflows , including running training jobs, generating evaluation metrics, and analyzing model performance. • Translate ML evaluation results and model metrics into actionable changes to dataset composition, simulation parameters, and data generation strategies. • Validate and quality-check synthetic datasets prior to hand-off, ensuring generated data meets required specifications and quality standards. • Develop, maintain, and improve simulation tooling, automation, and dataset generation scripts . • Work with large-scale datasets, including dataset storage, organization, versioning, and reproducibility . • Troubleshoot simulation, data generation, and ML pipeline issues across Linux-based development environments. • Collaborate cross-functionally with camera architects, computer vision engineers, ML engineers, and other technical stakeholders to support perception and imaging development. Must Have Qualifications • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field . • 5+ years of software engineering experience , with significant experience supporting or designing ML infrastructure and data pipelines . • 5+ years of hands-on Python and C++ development . • Strong understanding of camera and sensor simulation fundamentals , including: • Camera intrinsic and extrinsic parameters • Camera setup and calibration • Sensor modeling • Noise sources and sensor characteristics • Conversion gain • Quantum efficiency • Read noise and shot noise • Basic ISP concepts and image formation • Experience running machine learning training and evaluation workflows , preferably using PyTorch . • Ability to interpret model evaluation metrics and translate performance results into changes to datasets or simulation configurations. • Experience with large-scale synthetic dataset generation, storage, management, and versioning . • Familiarity with Linux development environments and source control systems . • Experience building ML models, ML pipelines, or ML infrastructure . • Practical understanding of how camera and sensor simulation systems generate data for computer vision applications. • Previous AI/ML experience , including experience contributing to or developing ML architectures and pipelines. Preferred Qualifications • Experience with rendering engines or simulation frameworks , including Blender, Unreal Engine, Unity , or proprietary/in-house simulation platforms. • Background in optics, imaging, or computational photography , including concepts such as: • Radiometry • Point Spread Function (PSF) • Modulation Transfer Function (MTF) • Experience with camera or ISP tuning . • Experience developing or evaluating computer vision and perception models . • Experience working with synthetic data for computer vision, imaging, robotics, AR/VR, autonomous systems, or related applications . • Experience optimizing simulation pipelines for large-scale or automated dataset generation . Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, qualified applicants will be considered for assignment with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, meet client expectations, standards, and accompanying requirements, and safeguard business operations and company reputation. #TMMT

Requirements

Must-haves

Simulation Computer Vision or ML Engineer
Location: Sunnyvale, CA — Hybrid, 3 days onsite per week
Compensation: $95 - $100/hr on W2
Contract Duration: 12 Months with potential extension
We are looking for a Simulation CV/ML Engineer to help build and operate camera and sensor simulation pipelines that enable next-generation computer vision and machine learning development.
Run, maintain, and iterate on camera and sensor simulation pipelines to generate synthetic datasets on demand.
Configure simulation scenes, camera parameters, and sensor models based on customer and camera architect specifications.
Deliver high-quality training and evaluation datasets to camera architecture, ML, and perception teams within tight development timelines.
Support ML model training and evaluation workflows , including running training jobs, generating evaluation metrics, and analyzing model performance.
Translate ML evaluation results and model metrics into actionable changes to dataset composition, simulation parameters, and data generation strategies.
Validate and quality-check synthetic datasets prior to hand-off, ensuring generated data meets required specifications and quality standards.
Develop, maintain, and improve simulation tooling, automation, and dataset generation scripts .
Work with large-scale datasets, including dataset storage, organization, versioning, and reproducibility .
Troubleshoot simulation, data generation, and ML pipeline issues across Linux-based development environments.
Collaborate cross-functionally with camera architects, computer vision engineers, ML engineers, and other technical stakeholders to support perception and imaging development.
Must Have Qualifications

Nice-to-haves

Experience with rendering engines or simulation frameworks , including Blender, Unreal Engine, Unity , or proprietary/in-house simulation platforms.
Background in optics, imaging, or computational photography , including concepts such as:
Point Spread Function (PSF)
Modulation Transfer Function (MTF)
Experience with camera or ISP tuning .
Experience developing or evaluating computer vision and perception models .
Experience working with synthetic data for computer vision, imaging, robotics, AR/VR, autonomous systems, or related applications .
Experience optimizing simulation pipelines for large-scale or automated dataset generation .

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Keywords to mirror

mlmachine learningpythonai

Platform: jobdiva
Effort: medium

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