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Applied Scientist II, Perception

Amazon.com Inc

  • San Francisco, CA
  • 30+ days ago

    Highlights

    You will develop and deploy state-of-the-art perception algorithms that enable robots to truly understand and interact with the physical world - bridging the gap between theoretical research and real-world impact. At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world.

    Numbers & Facts

    LocationSan Francisco, CA
    IndustryRetail
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles

    Description

    Amazon is on a mission to redefine the future of automation - and we"re looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments.

    At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence - and we"re just getting started.

    As a Applied Scientist in Robot Perception, you will be at the forefront of this transformation. You will develop and deploy state-of-the-art perception algorithms that enable robots to truly understand and interact with the physical world - bridging the gap between theoretical research and real-world impact. Bringing deep expertise in Computer Vision and a nuanced understanding of the capabilities and limitations of modern Vision-Language Models (VLMs), you will innovate boldly and push the boundaries of what"s possible. Our vision for the Perception layer is ambitious: to enable seamless, intelligent interaction between the user, the robot, and its environment.

    This is a rare opportunity to work at the intersection of deep learning, large language models, and robotics - contributing to research that doesn"t just advance the field, but reshapes it. You will collaborate with world-class teams pioneering breakthroughs in dexterous manipulation, locomotion, and human-robot interaction, all at an unprecedented scale.

    Join us in building intelligent robotic systems that will define the future of automation and human-robot collaboration.

    Key job responsibilities

    • Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding
    • Lead research initiatives in computer vision, sensor fusion and 3D perception
    • Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities
    • Drive end-to-end ownership of ML models - from data collection and labeling strategy to training, evaluation, and deployment
    • Mentor junior scientists and engineers; contribute to a culture of technical excellence
    • Define and track key metrics to measure perception system performance in real-world environments
    • Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents

    A day in the life

    • Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment
    • Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations
    • Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed - and in doing so, build lasting trust across the team
    • Mentor team members while maintaining significant hands-on contribution to technical solutions

    About Company

    At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

    Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

    It’s Always Day 1
    At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

    Our Leadership Principles
    Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

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