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
- Competitive salary, meaningful growth path toward CV Lead / Architect as the team scales
- Equity in our growth story and growing with us.
How to Apply
Apply via the form linked — include your resume and be ready to talk through a real production CV problem you've solved.
Neurabit is an equal opportunity employer.