Perception Engineer

We are seeking an experienced, product-focused Perception Engineer (4–7 years of experience) to own, evolve, and scale the perception stack powering our autonomous home security hardware.

This is an applied, production-first engineering role. You won't be doing theoretical lab research—you will own the end-to-end perception pipeline and ship real-time computer vision models, video ingestion frameworks, and tracking algorithms directly onto NVIDIA edge hardware (Jetson Thor/Orin) deployed in the field.

Key Responsibilities

• Perception Architecture: Re-architect and optimize our core perception services running on NVIDIA Thor to support increased camera stream capacity, lower latency, and maximize pipeline stability.
• Model Optimization & Deployment: Evaluate, swap, and deploy faster, higher-performing deep learning models (e.g., PyTorch to TensorRT conversion) while maintaining real-time performance limits on edge hardware.
• 3D Perception & Tracking: Implement monocular depth estimation onto the NVIDIA Thor platform to enable robust 3D tracking of people and vehicles across property boundaries.
• Pipeline Engineering: Work deeply with NVIDIA DeepStream, GStreamer, and FFmpeg to build and maintain high-throughput video ingestion and media processing pipelines.
• Cross-Functional Execution: Collaborate directly with device, hardware, and systems engineering teams to unblock dependencies and push reliable software updates to customer units.

What We're Looking For

Requirements

• Experience: 4–7 years of hands-on experience building and deploying applied perception or machine learning systems in production at a Series A–D startup or high-growth tech environment.
• Core Languages: Advanced proficiency in C++ (C++20 preferred) and Python .
• NVIDIA Edge Stack: Direct experience deploying on edge hardware using NVIDIA DeepStream, GStreamer, TensorRT, and JetPack (ideally Jetson Orin or Thor).
• Domain Background: Background in computer vision for physical hardware products in safety-critical or hardware-adjacent fields (e.g., robotics, autonomous vehicles, aerospace, or physical security).
• Video & Media Pipelines: Strong knowledge of video streaming formats, camera feeds, multi-object tracking, and multi-camera association.

Tech Stack

• Languages: C++20, Python
• ML & Edge Frameworks: NVIDIA DeepStream, TensorRT, PyTorch, CUDA, JetPack, gRPC, Abseil, CMake
• Media & Video Processing: GStreamer, FFmpeg