Simulation CV/ML Engineer

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