Job Description

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 Research, 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 augmented reality device that can enable high-quality contextually relevant interactions across a range of complex, dynamic, real-world tasks in natural environments; to achieve this goal, our team draws on methods and knowledge from artificial intelligence, machine learning, computer vision, and human–computer interaction. We are looking for a skilled and motivated Research Science Manager with expertise in leading strategy and directing teams in multimodal machine learning, sensor fusion, gesture recognition, contextual modeling or related fields to join our team. More broadly, the chosen candidate will work with a diverse and highly interdisciplinary team of researchers and engineers and will have access to cutting edge technology, resources, and testing facilities.

In this position, you will work with an interdisciplinary team of domain experts in embodied artificial intelligence (AI), human–computer interaction, computer vision, cognitive and perceptual science, and sensing and tracking on problems that contribute to creating human-centered contextual interactive systems. The position will involve building, leading, and directing a team that develops full multimodal ML technology stacks—leveraging video, audio, IMU, EMG, optical-sensor, and other wearable sensor data—to enable recognition of a diverse library of gestures from a rich ecosystem of wearable devices. The position will also involve leading strategy and cross-functional workstreams centered on uncovering contextually relevant information for predicting user behavior from wearable sensors. The ML models built by this portfolio of work will leverage large-scale real-world data sets and the scale of Facebook machine-learning infrastructure, and will be deployed into AR/VR prototypes to uncover research questions on the path to the next era of human-centered computing.

Responsibilities

• Lead strategy and cross-functional workstreams centered on uncovering contextually relevant information for predicting user behavior from wearable sensors
• Define and execute a cutting-edge applied research program toward developing full multimodal ML technology stacks to enable recognition of a diverse library of gestures from wearable sensors
• Direct and manage a team of research scientists and engineers working on advancing AR/VR, including creating career development plans, managing performance, and conducting performance reviews
• Provide team guidance, regular feedback, education, coaching, and mentoring
• Identify, recruit, interview, and hire new research scientists and engineers
  

Minimum Qualification

• PhD degree in computer science, signal processing, machine learning, artificial intelligence, or related technical field
• Demonstrated track record in defining and leading applied research in multimodal machine learning, sensor fusion, gesture recognition, or related areas
• 5+ years of experience in managing teams and working in a cross-functional setting
• 5+ years of experience building, testing, and deploying machine-learning/AI systems in real-time, interactive applications, and developing a new algorithm tailored solution to challenging real-world problems
  

Preferred Qualification

• Experience in building machine-learning systems that leverage wristband sensors
• Experience with machine learning applied to electromyograph (EMG) signals
• Experience with sensor systems and joint hardware/algorithm design
• Experience with hand or body tracking, state of the art machine-learning models for time-series modeling (e.g. inertial, audio, video), and human-computer interaction
• Familiarity with concepts in embodied AI, representation learning, and few shot learning
  

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 accommodations-ext@fb.com.