KeyMe is reinventing the $12 billion locksmith services industry with advanced robotics and AI, building the world’s most trusted brand in “access solutions”. Our network of self-service kiosks are located in thousands of retail locations across the country (IKEA, Bed Bath & Beyond, Albertsons, Kroger, RiteAid, Menards, etc.) supporting duplication of brass keys as well as sophisticated electronic keys such as RFID and vehicle transponder keys. Our kiosks are complemented by KeyMe locksmiths who provide unrivaled service quality for emergency lockouts and other skilled access and home services.
KeyMe is growing rapidly and has raised over $100M from top-tier investors like BlackRock, Comcast Ventures, and Battery Ventures.
About the Role
KeyMe sits at the intersection of machine learning, computer vision, software, and mechanical design. Our robotic self-service kiosks scan and duplicate thousands of keys per day.
Our machine intelligence team is looking for a Machine Learning Engineer to help keep our thousands of robotic kiosks functioning correctly. Reporting to the Director of Machine Intelligence you will work on our computer vision applications including object classification, segmentation and localization.
KeyMe engineering manages a massive surface area -- from kiosk touchscreen UX, to backend order management tools, to robotics and embedded systems, to data engineering and analysis. You’ll get to leverage your skills against a diverse problem set alongside smart, motivated colleagues who want to win. We offer an extremely broad range of engineering activities that ensure you’ll never be bored in your career.
What You'll Be Doing:
You will be implementing deep learning architectures from first principles.
Read the latest related publications and come up with innovative solutions to the problem at hand.
How We Know You Can Do It:
1-2 years developing deep learning applications for computer vision
Familiarity with libraries like OpenCV
Strong understanding of a modern programming language, preferably Python
Knowledge of at least one machine learning framework (e.g. Tensorflow)
Experience with git or other DVCS
Masters degree in Computer Science or a related field or equivalent experience
Experience in developing machine learning applications
AWS and docker skills are desired but not required.