Perception Engineer – Computer Vision & Edge AI

About the Role

As a Perception Engineer, you'll build and own the computer vision systems powering autonomous robots deployed in real-world environments. You'll transform state-of-the-art AI models into reliable production systems capable of detecting, tracking, and understanding objects across multiple cameras while running efficiently on edge hardware.

This is a builder's role where success is measured by real-world performance, not research papers. You'll work closely with AI, Robotics, and Software Engineering teams to deliver perception systems that operate reliably in demanding production environments.

What You'll Do

• Design and deploy cross-camera object re-identification (ReID) systems for people and vehicles
• Build high-performance object detection and multi-object tracking pipelines
• Integrate Vision-Language Models (VLMs) for scene understanding and operator intelligence
• Develop robust real-time video pipelines using RTSP and WebRTC
• Optimize AI models for NVIDIA Jetson and edge devices using TensorRT, quantization, pruning, and latency optimization
• Evaluate, fine-tune, and train computer vision models where required
• Build scalable image and video data pipelines for training and evaluation
• Collaborate closely with Robotics and Software Engineering teams to integrate perception into autonomous systems
• Continuously improve model reliability, performance, and deployment efficiency

What We're Looking For

• 3+ years of experience building and deploying production Computer Vision or Machine Learning systems
• Strong expertise in object detection, multi-object tracking, and cross-camera ReID
• Hands-on experience with Vision-Language Models (VLMs)
• Experience building real-time multi-camera video processing pipelines using RTSP and WebRTC
• Proven experience deploying AI models on edge hardware using TensorRT, quantization, pruning, or similar optimization techniques
• Strong Python and PyTorch (or JAX) skills
• Experience building reliable ML systems with strong software engineering practices
• Experience managing large image and video datasets for training and evaluation
• Builder mindset with strong ownership and the ability to thrive in a fast-moving startup environment

Nice to Have

• NVIDIA DeepStream
• MLOps (model versioning, CI/CD, monitoring)
• RAG and LLM-based systems
• Robotics, autonomous systems, surveillance, or defense
• Edge AI deployment
• Air-gapped or on-premise environments
• Publications in CVPR, ICCV, NeurIPS, or ICLR

What We Offer

• Competitive salary with meaningful equity
• Visa and relocation support
• Work alongside world-class founders and AI researchers
• Significant ownership over the perception stack from day one
• Opportunity to build production AI systems deployed in the physical world
• International, collaborative, engineering-first culture
• Direct impact on the future of autonomous robotics and intelligent security