New

Software Engineer III - Simulation CV/ML Engineer

Spectraforce Technologies
United States, California, Sunnyvale
Sep 24, 2026
Job Title: Software Engineer III - Simulation CV/ML Engineer Duration: 12 Months Location: Sunnyvale, CA (hybrid - 3 days onsite) Responsibilities: Run and iterate on camera/sensor simulation pipelines to generate synthetic datasets on demand Deliver training/evaluation data to camera architects and ML teams under tight timelines Support ML algorithm training and evaluation using the generated synthetic data - run training jobs, produce evaluation metrics, and iterate on dataset composition based on model performance Configure simulation scenes and sensor parameters to match customer/architect specifications Validate and quality-check generated data before hand-off Maintain and improve simulation tooling and dataset generation scripts Top 3 must-have HARD skills: Minimum Qualifications Bachelor's degree in computer science or a related field. Minimum 5+ years of experience in software engineering, with a focus on ML infrastructure design. 5+ years' experience in Python and C++. Camera & sensor simulation fundamentals: Camera intrinsic/extrinsic setup and calibration Sensor modeling: noise sources, conversion gain, quantum efficiency, read/shot noise Basic understanding of ISP and image formation ML training & evaluation Experience running ML training/evaluation workflows (PyTorch preferred) Able to interpret model metrics and translate them back into dataset changes Data handling: comfortable with large-scale dataset generation, storage, and versioning Familiarity with Linux dev environments and source control Experience building ML models and pipelines Understanding how camera simulations work Previous AI experience to develop ML architectures Good to have skills: Preferred Qualifications Experience with rendering engines (Blender, Unreal, Unity) or in-house simulation frameworks Optical/imaging background (radiometry, PSF, MTF) Prior experience with camera/ISP tuning or perception model development Typical Day in the Role: Responsibilities Run and iterate on camera/sensor simulation pipelines to generate synthetic datasets on demand Deliver training/evaluation data to camera architects and ML teams under tight timelines Support ML algorithm training and evaluation using the generated synthetic data - run training jobs, produce evaluation metrics, and iterate on dataset composition based on model performance Configure simulation scenes and sensor parameters to match customer/architect specifications Validate and quality-check generated data before hand-off Maintain and improve simulation tooling and dataset generation scripts Minimum Qualifications: Bachelor's degree in computer science or a related field. Minimum 5+ years of experience in software engineering, with a focus on ML infrastructure design. 5+ years' experience in Python and C++. Camera & sensor simulation fundamentals: Camera intrinsic/extrinsic setup and calibration Sensor modeling: noise sources, conversion gain, quantum efficiency, read/shot noise Basic understanding of ISP and image formation ML training & evaluation Experience running ML training/evaluation workflows (PyTorch preferred) Able to interpret model metrics and translate them back into dataset changes Data handling: comfortable with large-scale dataset generation, storage, and versioning Familiarity with Linux dev environments and source control Experience building ML models and pipelines Understanding how camera simulations work Previous AI experience to develop ML architectures Preferred Qualifications: Experience with rendering engines (Blender, Unreal, Unity) or in-house simulation frameworks Optical/imaging background (radiometry, PSF, MTF) Prior experience with camera/ISP tuning or perception model development Interview process: 1 technical interview 1 Screening interview 30 mins for Screening and 45 mins for technical