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# Software Development Engineer II

- **Company:** Amazon.com, Inc.
- **Location:** North Reading, MA, United States
- **Experience:** Experienced
- **Salary:** $143,700.0 - $194,400.0
- **Contract:** Permanent contract
- **Skills:** Computer Vision, C++ (Programming Language), Nvidia CUDA, Software Debugging, Software Design Documents, Middleware, Hardware-In-The-Loop Simulation, Python (Programming Language), Machine Learning, Object Detection, Model Compression, Software Engineering, Management of Software Versions, Graphics Processing Unit (GPU), Robot Operating System, Test-Driven Development (TDD), Deep Learning, Discretization, Real-time Inference, ONNX (Open Neural Network Exchange) Format, Triton Inference Server, Machine Learning Operations, TensorRT, NVIDIA Jetson
- **Published:** October 11, 2026
- **Apply:** https://dejobs.org/x/x/FA07B79AE3D345DF902C98D511C4208C/job/

## About the Role

* Knowledge of Python and/or C++ programming
 * 4+ years in CS, ME, EE or related field experience
 * Experience with robotics middleware like ROS2, ZCM, Zenoh, etc.
 * Experience developing or integrating perception, computer vision, SLAM, or navigation software for robots or other real-world embedded systems
 * Experience deploying and optimizing machine learning models for real-time inference on embedded or edge GPUs (e.g., NVIDIA Jetson), using tools such as TensorRT, ONNX Runtime, or CUDA
 * Experience with test driven development (TDD) in robotics software, * Master's degree or PhD in Robotics, CS, EE, or a related field, with a focus on computer vision or machine learning
 * Experience partnering with applied scientists to take research models from prototype to production, including improving their performance on real-world data
 * Experience with 3D perception and state estimation, such as stereo depth, visual or visual-inertial odometry, SLAM, mapping, or localization
 * Experience integrating perception into navigation or autonomy stacks (e.g., ROS 2, Nav2, occupancy or costmap generation)
 * Experience with model compression and quantization (post-training and quantization-aware, INT8/FP8, pruning, distillation) and GPU profiling tools such as NVIDIA Nsight Systems or Nsight Compute
 * Experience with multi-camera and multi-sensor pipelines (e.g., GMSL cameras, lidar) and serving multiple models on shared accelerators (e.g., Triton Inference Server)
 * Experience deploying models across heterogeneous accelerator platforms (GPU, NPU, DSP)
 * Experience building simulation-based or hardware-in-the-loop evaluation for perception systems
 * Excellent collaboration and communication skills, with the ability to work across science and engineering teams

## Description

* Partner with perception, SLAM, and navigation scientists and engineers to integrate their models and algorithms (e.g., stereo depth, object detection and segmentation, visual-inertial odometry, mapping, and localization) into the on-robot software stack
 * Optimize deep learning models and computer vision pipelines for real-time inference on embedded GPUs, using techniques such as quantization, pruning, graph optimization, and inference-engine tuning
 * Profile and reduce end-to-end perception latency, throughput, and memory use from sensor input to model output, including when multiple models share the same GPU
 * Build efficient multi-camera and multi-sensor data paths, including zero-copy and hardware-accelerated pre- and post-processing, together with sensor-interface and model-serving owners
 * Build and own evaluation datasets, metrics, and regression gates (precision, recall, accuracy, latency) across offline, simulation, and hardware-in-the-loop testing, and use them with science partners to drive measurable accuracy improvements
 * Make perception components production-ready with versioning, configuration, health monitoring, and telemetry, and debug failures observed on real robots
 * Write design documents and experiment reports that clearly communicate tradeoffs, results, and limitations to science, engineering, and program stakeholders