Senior Computer Vision Engineer

About Neurabit Neurabit is a bootstrapped, DPIIT-recognised, deep-tech company building edge AI, computer vision, and physical AI systems that run where the internet doesn't. Our systems are deployed across 7+ countries — from passenger analytics on public transit fleets to industrial safety monitoring, substation surveillance, and sports analytics. We're a team of ~18 engineers who ship real hardware-software systems into messy, real-world environments: moving buses, dusty factory floors, remote substations. We're not a research lab. Models here don't live in notebooks — they live on Jetsons bolted inside vehicles and on factory walls, running 24/7. The Role You'll own computer vision systems end to end: from architecture and model selection through optimization, edge deployment, and production hardening. You'll work directly with the founding team on flagship projects — multi-camera passenger counting, PPE and zone compliance detection, ANPR, crowd intelligence, and driver monitoring — and your decisions will ship to paying customers within weeks, not quarters. What You'll Do - Design and ship multi-camera CV pipelines for detection, tracking, and counting in constrained edge environments - Build and tune object tracking systems (ByteTrack, DeepSORT, or similar) for occlusion-heavy, real-world scenes - Optimize models for edge inference — quantization, pruning, TensorRT/ONNX conversion — targeting NVIDIA Jetson (Orin/Xavier/Nano), Hailo, and similar accelerators - Own accuracy in the field: design evaluation protocols, debug failure modes from real deployment footage, and close the gap between lab metrics and production performance - Work with RTSP/RTMP camera streams, handle unreliable networks, and build pipelines that degrade gracefully - Write clean, maintainable Python/C++ and mentor mid-level engineers on CV best practices - Collaborate with hardware, backend, and product teams to scope what's technically feasible before we commit it to a client Must-Haves - 4+ years of production computer vision experience — models you built are (or were) running in live deployments, not just demos or papers - Deep hands-on experience with detection and tracking: YOLO family, transformer-based detectors, multi-object tracking - Proven edge deployment experience: TensorRT, ONNX Runtime, OpenVINO, or DeepStream on Jetson-class hardware - Strong Python; working C++ for performance-critical paths - Solid grasp of the full pipeline: data collection, annotation strategy, training, evaluation, deployment, and monitoring - Experience debugging CV systems from field footage — you know that production accuracy problems are rarely solved by "train a bigger model" - Comfort with Linux, Docker, and Git-based workflows Nice-to-Haves - Video analytics at scale: GStreamer, FFmpeg, MediaMTX, or VMS integration - Re-identification, pose estimation, or face recognition in production - Experience with counting/occupancy systems, ANPR, or industrial safety CV - Familiarity with camera hardware: ONVIF, RTSP tuning, lens/FOV selection, IR/low-light constraints - Exposure to MLOps for edge fleets: OTA model updates, remote monitoring, telemetry - Contributions to open-source CV projects Why Neurabit - Real ownership — you'll be the senior-most CV voice in the company, shaping architecture decisions across every project - Ship fast, see impact — your work goes live on buses, in factories, and at government sites within weeks - Hard problems — edge constraints, moving cameras, occlusion, low light — the kind of CV that doesn't have a Kaggle solution - Build from Bharat — we're proving world-class deep tech can be built from a Tier 3 city and shipped to 7+ countries - Competitive salary, meaningful growth path toward CV Lead / Architect as the team scales