Software Development Engineer, Last Mile Delivery, Edge Intelligence
Amazon
- Location
- US, CA, Santa Clara
- Employment
- Full Time
- Work model
- On-Site
- Level
- Mid
- Posted
- 5d ago
Skills
About this role
The Edge Intelligence team, part of Amazon's Connected Vehicles organization within Last Mile Technology, builds and operates real-time intelligence, perception, and camera/sensor fusion systems that run directly on deployed delivery devices. We bridge embedded hardware and cloud platforms to enable low-latency, reliable, and scalable intelligence at the edge, powering the in-vehicle experiences that keep drivers safe and deliveries efficient. We are building the next generation of smart delivery vehicles, both traditional and electric, combining IoT technologies, real-time data streams, and machine learning to deliver faster, safer, and better. Key job responsibilities * On-Device Applications: Design and develop applications that power in-vehicle experiences, improve safety, and enhance delivery efficiency across multiple device platforms * Edge Inference & ML: Build and optimize on-device inference pipelines for perception, sensor fusion, and real-time decision-making models, ensuring low-latency and high-reliability performance on resource-constrained hardware * Sensor & Camera Processing: Develop sensor ingestion frameworks and camera/signal processing pipelines that fuse data from multiple modalities (cameras, LiDAR, telematics, GPS) into actionable intelligence * Edge Runtime Optimization: Profile and optimize edge compute workloads for performance, memory, power consumption, and thermal constraints across heterogeneous hardware platforms * Device-to-Cloud Orchestration: Design and implement data pipelines that efficiently move telemetry, video, and sensor data from edge devices to cloud analytics platforms, balancing bandwidth, latency, and cost * Edge Telemetry & Observability: Build monitoring, logging, and alerting systems that provide real-time visibility into the health and performance of thousands of deployed edge devices * On-Device Map-Making: Contribute to on-device map-making models and localization systems that enable vehicles to understand and navigate their environment * Operational Excellence: Own the end-to-end lifecycle of your systems — from design and implementation through deployment, monitoring, and on-call support