Lead - Computer Vision & AI Architect

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. You will mentor a small, senior team through design and code review — formal people management is not the core of the role today, but technical leadership and delivery ownership are.

Key Responsibilities

1. Technical Leadership & Execution Ownership

• Technical Direction: Set and own architecture decisions across 3D pose, multi-camera geometry, body/mesh modeling, form evaluation, and edge deployment — and be accountable for their trade-offs.
• Product Ownership: Translate product goals into clear module-level requirements, scope, priorities, and acceptance criteria for the perception program; decide what ships and what defers.
• Execution Management: Plan and run sprints, sequence cross-module work, and manage delivery against milestones and measurable KPIs (latency, frame rate, calibration repeatability, demo reliability).
• Engineering Practice: Foster clean coding, thoughtful design and code reviews, automated testing, clear documentation, and reproducible experiment tracking. Mentor CV and AI/ML engineers technically.

2. System Architecture & Cross-Functional Coordination

• System Coherence: Own end-to-end architecture coherence across capture, perception, edge runtime, mobile app, and cloud — not just the CV core, but how the whole movement-intelligence loop connects.
• Interfaces & Dependencies: Define and manage cross-module interface contracts and dependencies so parallel workstreams integrate cleanly.
• Cross-Functional Bridge: Coordinate day-to-day across full-stack engineering, UI/UX, CV and ML/CV engineers, and — as the team grows — edge/embedded and hardware/firmware engineers, plus partner integrations.
• Performance Budgets: Establish and enforce real-time latency, frame-rate, memory, and thermal budgets across edge hardware, smart glasses, Linux workstations, and NPUs — from current real-time demo targets (sub-second feedback at 10–15 FPS on Jetson-class simulation) toward productization targets (sub-200ms feedback at 30–60 FPS).

3. Hands-On Computer Vision & 3D Geometry

• Multi-View Geometry & 3D Pose: Lead hands-on development of camera calibration, multi-camera synchronization, epipolar geometry, 3D joint triangulation, and temporal smoothing across a multi-camera capture rig.
• Personalized Body Modeling & Form Evaluation: Build pose-to-mesh alignment against a user-specific skeletal/mesh model and a live form-comparison engine that turns movement variance into timely, trustworthy corrective cues.

4. Multimodal AI & Edge Deployment

• Multimodal AI: Guide evaluation and fine-tuning (LoRA/QLoRA) of Vision-Language Models (e.g. LLaVA, Qwen-VL) for movement interpretation and coaching dialogue.
• Edge Optimization: Oversee quantization (INT8/FP16) and export to ONNX, TensorRT, TFLite, or CoreML, and real-time inference on Jetson-class edge and NPU targets.

5. R&D and Intellectual Property

• Patent-Protected Innovation: Help build and document patentable core technology in mirror-aware tracking, personalized 3D motion reconstruction, and real-time form evaluation.

What We Are Looking For

Experience & Leadership

• Background: 7–10 years in computer vision, AI, or ML engineering, with a track record of owning technical direction and architecture on complex, real-time systems.
• Hands-On + Coordination: Demonstrated ability to stay deeply hands-on in code while also leading architectural reviews, driving execution, and coordinating delivery across cross-functional teams.
• Delivery: Proven record of shipping complex engineering projects against deadlines, with rigorous benchmarking and clear technical decision-making.

Computer Vision & 3D Geometry

• Core Math: Strong grasp of 3D geometry (rigid-body transforms, quaternions, rotation matrices) and projective geometry (calibration, bundle adjustment, triangulation).
• Pose Systems: Practical experience with 2D/3D pose models (e.g. ViTPose, HRNet, RTMPose, MediaPipe) and multi-camera setups.
• Toolkit: High proficiency in Python (NumPy, SciPy), OpenCV, and performance-oriented C++.

AI/ML & Multimodal AI

• Frameworks: Strong experience with PyTorch and Hugging Face Transformers.
• Multimodal Models: Hands-on work evaluating and fine-tuning Vision-Language Models (VLMs).
• Agentic AI: Familiarity with agent systems, tool calling, or Retrieval-Augmented Generation (RAG) is a plus.

Edge & Deployment

• Hardware Targets: Experience delivering real-time models to mobile SoCs, NPUs, smart glasses, or embedded hardware.
• Optimization Tools: Hands-on experience with TensorRT, ONNX Runtime, TFLite, or CoreML.

Nice to Have

• Education: Master's or Ph.D. in Computer Science, Computer Vision, Machine Learning, or a related field.
• Publications or Patents: Work published at CVPR, ICCV, ECCV, or NeurIPS, or granted patents.
• Domain Experience: Familiarity with biomechanics, fitness technology, sports analytics, or AR/VR.