Computer Vision Engineer

Skip to main content Computer Vision Engineer Meta Burlingame, CA Apply Join or sign in to find your next job Join to apply for the Computer Vision Engineer role at Meta Email or phone Password Show Forgot password? Sign in Sign in with Email or New to LinkedIn? Join now By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy. Computer Vision Engineer Meta Burlingame, CA 1 week ago 92 applicants See who Meta has hired for this role Apply Join or sign in to find your next job Join to apply for the Computer Vision Engineer role at Meta Email or phone Password Show Forgot password? Sign in Sign in with Email or New to LinkedIn? Join now By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy. Save Report this job Meta provided pay range This range is provided by Meta. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range $183,997.00/yr - $257,000.00/yr Meta Reality Labs is seeking a Machine Learning Engineer to drive the productization of gesture recognition models for our AR/VR devices. This role bridges research and production—you'll take ML models from development through deployment, collaborating across teams to ship gesture-based interactions on Quest and Meta Glasses. This is not a pure research position; we're looking for someone who thrives at turning cutting-edge ML into real products that reach millions of users.Computer Vision Engineer Responsibilities:Own end-to-end development of gesture recognition ML models from prototyping to production deployment on AR/VR devicesCollaborate with cross-functional teams including research, hardware, product, and platform engineering to integrate models into shipping productsOptimize ML models for on-device performance, balancing accuracy, latency, and power constraintsPartner with Reality Labs Research (RL-R) to translate research breakthroughs into production-ready solutionsDefine technical direction and mentor engineers on ML productization best practicesMinimum Qualifications:Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experienceBachelor's degree in Computer Science, Computer Engineering, Machine Learning, or equivalent practical experienceExperience shipping ML models to productionBackground in computer vision or machine learning, with focus on areas such as gesture recognition, pose estimation, or object trackingExperience with model optimization for edge/on-device deploymentTrack record of cross-functional collaboration to deliver ML-powered featuresPreferred...