Role Overview :

We are looking for a Lead Computer Vision & AI Architect to own the technical direction of our core perception stack while staying deeply hands-on. You will lead the design of our real-time movement-perception system - multi-camera geometry, 3D pose and mesh estimation, personalized body modeling, live form evaluation, Vision-Language coaching models, and edge deployment - and you will also carry end-to-end responsibility for how these pieces fit together as one coherent system across capture, edge runtime, mobile app, and cloud.

This is a hybrid technical-lead and product-ownership role, not a pure people-management position. You will set the perception roadmap, own module-level requirements and acceptance criteria, plan and run execution, and act as the primary technical bridge across engineering, design, hardware, and partner integrations.

Key Responsibilities :

- Technical Direction: Set and own architecture decisions across 3D pose, multi-camera geometry, body/mesh modeling, form evaluation, and edge deployment.
- Product Ownership: Translate product goals into clear module-level requirements, scope, priorities, and acceptance criteria.
- Execution Management: Plan and run sprints, sequence cross-module work, and manage delivery against milestones and KPIs.
- System Coherence:



Own end-to-end architecture coherence across capture, perception, edge runtime, mobile app, and cloud.
- Hands-On CV: Lead development of camera calibration, multi-camera synchronization, epipolar geometry, 3D joint triangulation, and temporal smoothing.
- Multimodal AI: Guide evaluation and fine-tuning (LoRA/QLoRA) of Vision-Language Models (e.g. LLaVA, Qwen-VL) for movement interpretation and coaching.

What We Are Looking For:

- Background: 7-10 years in computer vision, AI, or ML engineering, with a track record of owning technical direction on complex, real-time systems.
- Core Math: Strong grasp of 3D geometry (rigid-body transforms, quaternions, rotation matrices) and projective geometry.
- Toolkit: High proficiency in Python (NumPy, SciPy), OpenCV, and performance-oriented C .
- AI/ML Frameworks: Robust experience with PyTorch and Hugging Face Transformers.
- Edge Optimization: Hands-on experience with TensorRT, ONNX Runtime, TFLite, or CoreML for real-time inference on Jetson-class edge and NPU targets.

Nice to Have:

- Education: Master's or Ph.D. in Computer Science, Computer Vision, Machine Learning, or a related field.
- Domain Experience: Familiarity with biomechanics, fitness technology, sports analytics, or AR/VR.

📌 Lead Computer Vision & AI Architect (India)
🏢 Eonix Partners
📍 India