Role at a glance
- Job function
-
AI & Data Computer Vision Engineering
- Salary
- Not Disclosed
- Location
- North Reading, Massachusetts, United States
- Work arrangement
- On-site
- Education
- Master's, PhD
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We’ll check it against the original posting.
Qualifications
Required
- 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
Preferred
- 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
About the role
Original posting provided by amazon
Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of the latest software and AI tools for robots.
At Amazon we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence.
We are building the brains of our next-generation robots - a stack that:
- Enables deployment of robots at Amazon scale
- Enables unprecedented generalization across diverse tasks
- Seamlessly integrates with large models and optimal control techniques
- Integrates with human-safe safety solutions
As a Software Development Engineer on our on-robot software team, you will partner closely with applied scientists and engineers working on perception, localization and mapping (SLAM), and navigation to integrate their models and algorithms into the robot's onboard software, make them run in real time on embedded GPUs, and measurably improve their performance on real robot data. You will work at the boundary between science and engineering: turning research prototypes into fast, reliable, and observable on-robot components, and building the evaluation loops that show whether a change actually made the robot better.
Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration.
Key job responsibilities
- 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
- 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
- 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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
USA, MA, N.Reading - 143,700.00 - 194,400.00 USD annually
At Amazon we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence.
We are building the brains of our next-generation robots - a stack that:
- Enables deployment of robots at Amazon scale
- Enables unprecedented generalization across diverse tasks
- Seamlessly integrates with large models and optimal control techniques
- Integrates with human-safe safety solutions
As a Software Development Engineer on our on-robot software team, you will partner closely with applied scientists and engineers working on perception, localization and mapping (SLAM), and navigation to integrate their models and algorithms into the robot's onboard software, make them run in real time on embedded GPUs, and measurably improve their performance on real robot data. You will work at the boundary between science and engineering: turning research prototypes into fast, reliable, and observable on-robot components, and building the evaluation loops that show whether a change actually made the robot better.
Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration.
Key job responsibilities
- 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
Basic Qualifications
- 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
Preferred Qualifications
- 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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, MA, N.Reading - 143,700.00 - 194,400.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.