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Tier-1 employer, mid-level (3–6yrs) role, metro Bangalore increases applicant density despite specialization.
Core ML/CV skills are transferable, but automotive ISP and safety process requirements increase domain bias.
Explicit 3–6 years, mandatory CV/ML skills, PyTorch expertise, and automotive safety/process requirements raise filtering rigor.
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Own end-to-end design and implementation of perception algorithms for AI production stack in next-gen vehicles.
Research, benchmark SOTA perception algorithms, and develop compute-efficient computer vision solutions robust to diverse real-world conditions.
Debug and conduct root cause analysis ensuring performance, robustness, and reliability of perception algorithms across global cross-functional teams.
Bachelor’s or Master’s degree in Computer Vision, Computer Science, or related field.
3-6 years experience developing production-grade computer vision algorithms in real scenarios.
Strong skills in Python, OpenCV, SciPy, PyTorch, and knowledge of SOTA CNNs and ML/DL model training on large-scale datasets.
Strong understanding of Camera ISP pipelines (exposure control, gain, white balance) and impact on algorithm performance.
Experience delivering production-grade perception algorithms specifically in the automotive domain.
Strong foundational knowledge in perception, computer vision, deep learning, VLMs, and generative AI.
Experience optimizing models for deployment constraints on edge/embedded systems and working with diverse camera modalities (RGB, NIR, FIR, Depth).