ML Software Engineer, Robotics AI

Amazon's Vulcan team is seeking a talented ML Software Engineer to join their robotics division, focusing on creating premier robotic workcells. This role presents an exciting opportunity to work at the intersection of robotics, artificial intelligence, and computer vision.

The position involves building sophisticated systems that can perceive, learn, and act intelligently. You'll be responsible for developing computer vision systems, ML and AI models, robotic control and motion planning, and process management. The role encompasses end-to-end ownership of various aspects including decision explanation, fault detection, monitoring, A/B testing, large-scale model training, simulation, and hardware integration.

As a software engineer on the team, you'll have the unique opportunity to work on both prototype development in the lab and wide-deployment systems. You'll be instrumental in planning roadmaps, implementing services, and monitoring the robotic fleet. The role offers extensive learning opportunities as part of an interdisciplinary team building all aspects of the robot hardware and software stack.

The position requires strong technical expertise in software development and machine learning, with at least 3 years of professional experience. You'll be working in a collaborative environment, mentoring team members, and directly engaging with customers and partners to incorporate feedback into prototypes.

Amazon offers competitive compensation ranging from $129,300 to $223,600 based on location and experience, along with comprehensive benefits including medical, dental, vision coverage, parental leave, and a 401(k) plan. This is an excellent opportunity for someone passionate about robotics and AI to make a significant impact at one of the world's leading technology companies.

The role is based in Seattle, WA, and offers the chance to work on cutting-edge technology that will shape the future of robotics and automation. Join Amazon Robotics to be part of a team that's pushing the boundaries of what's possible in robotic systems.