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Tier-1 brand, Bangalore metro, and popular ML/AI title increase applicant density.
Automotive perception, ISP knowledge, and edge deployment requirements limit cross-industry transferability.
Explicit 1–2 years, mandatory CV/ML skills, automotive regulations and production constraints raise filter strictness.
Own the end-to-end design and implementation of perception algorithms in AI production stack for next-gen vehicle safety and decision-making systems.
Research and benchmark state-of-the-art perception algorithms to create novel, compute-efficient solutions robust to diverse real-world conditions.
Collaborate globally to ensure robust, scalable AI algorithms with thorough debugging, root cause analysis, and compliance to AI process standards like EU AI Act and ASPICE ML Process.
Bachelor's or Master's degree in Computer Vision, Computer Science, or related fields.
1-2 years of experience developing production-grade computer vision algorithms in real production scenarios.
Strong proficiency in Python and libraries such as OpenCV, SciPy, PyTorch; understanding of SOTA CNNs and ML/DL model training.
Experience with camera ISP pipelines and knowledge of AI process standards (e.g., EU AI Act, ASPICE ML Process).
Experience delivering production-grade perception algorithms in automotive domain with diverse camera modalities (RGB, NIR, FIR, Depth).
Demonstrated ability in optimizing ML models for runtime performance on edge or embedded systems.
Research contribution evidenced by publications in top-tier conferences/journals (e.g., CVPR, ICCV) or patents in automotive AI algorithms.