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. Sensor modeling: noise sources, conversion gain, quantum efficiency, read/shot noise.
Numbers & Facts
Location
Sunnyvale, CA
Salary
$95.75–$99.94 Per Year
Description
Our Client, an Internet Content & Information company, is looking for a Simulation CV/ML Engineer for their Sunnyvale, CA/Hybrid location.
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
Requirements:
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