Facebook’s mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we’re building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we’re creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities – we’re just getting started.
At Facebook Reality Labs, our goal is to explore, innovate and design novel interfaces and hardware for virtual, augmented, and mixed reality experiences. We are driving research towards a vision of an always-on AR device that can provide contextually relevant assistance across a range of complex, dynamic, real-world tasks in natural environments. To this end, we are seeking a Machine Learning Researcher with expertise in reinforcement learning, optimal control, dynamic programming, embodied artificial intelligence (AI), active/online learning, Markov decision processes, human–machine collaboration, or related fields.In this position, you will work with domain experts in embodied AI, computer vision, human–computer interaction, cognitive and perceptual science, and haptics on problems that contribute to creating goal-oriented contextual assistive systems. The position will involve conducting research in simulation environments (which will leverage the scale of Facebook machine-learning infrastructure), collecting large-scale real-world data sets, and deploying models in AR/VR prototypes to uncover research questions on the path to the next era of human-centered computing.
- Devise and execute cutting-edge research with interdisciplinary collaborators aimed at developing automated assistive interaction systems for complex tasks in the presence of uncertainty.
- Develop research-grade code for deployment in research prototypes.
- Work collaboratively to develop novel machine-learning models in service of a contextual AR assistant.
- Mentor MS/PhD interns and postdocs and collaborate with external academic groups to advance our research goals.
- Currently has, or is in the process of obtaining, a PhD degree or completing a postdoctoral assignment in the field of artificial intelligence, machine learning, computer science, computational science and engineering, operations research, or related areas.
- Expertise in at least two of the following areas: reinforcement learning, optimal control, dynamic programming, embodied AI, active/online learning, Markov decision processes, human–machine collaboration.
- Experience generating novel research questions that cross disciplinary boundaries and/or extend research to a new application domain.
- Experience working in a modern software development environment (e.g., unit testing, source control, continuous integration).
- Interpersonal experience: cross-group and cross-culture collaboration.
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
Facebook is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.
Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected]