As a Research Manager, you will be responsible for leading an applied research team of computer vision and machine learning scientist in planning, prototyping and delivering AR/AI products on mobile platforms. You will plan roadmaps, evaluate feasibility, and deliver experiences that our customers will love.
A successful candidate will have an established background in the computer vision/machine learning community, be familiar with the latest trends/technologies in the computer vision community, and have an understanding of what it takes to apply research to deliver products. You will be helping to hire and build your team, develop customer-facing experiences, manage your own projects, and communicate to members of the team who are not familiar with computer vision.
Key Responsibilities:
- Responsible for understanding feasibility on multiple research areas. Build roadmaps and milestones. Understand what works or won’t work.
- Management and execution against project plans and delivery commitments. Prioritize between research and applied research. Report on status, milestones and goals to management.
- Manage the day-to-day activities of the research team within an Agile/Scrum environment.
- Management of departmental resources, staffing, mentoring, and enhancing and maintaining a best-of-class research team
- Work closely with other computer vision teams and engineering teams to deliver working solutions to market.
- Stay up-to-date with trends, papers, and academia.
- 3-10+ years of industry experience in managing or leading computer vision/machine learning efforts.
- Doctoral Degree in Computer Science, Electrical Engineering or related field or Master’s Degree with at least 3 year’s experience.
- Deep theoretical knowledge and hands-on experiences in computer vision, image processing and machine learning. Breadth of knowledge in multiple computer vision areas.
- Solid research track record with peer-reviewed publications in top academic conferences and journals in the related areas.
- Excellence in technical communication with peers and non-technical cohorts. Able to explain complexity in easy-to-understand terms.
- Experience in building complex software systems involving computer vision that have been successfully delivered to customers.
- Experience running computer vision and image processing algorithms on mobile devices.
- Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Ability to rapidly prototype and evaluate customer applications and interaction methodologies.
- Experience in developing real-time systems