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 wrist-worn AR input device that enables rich user interactions across a range of complex, dynamic, real-world tasks in natural environments; We are looking for a skilled and motivated research engineer with expertise in real-time computer vision, machine learning, signal-processing, sensor fusion, or related fields to join our team. In this position, you will design, train, and evaluate models that infer human actions and input commands in real-time interactive systems, using data from wearable cameras and other sensors (e.g., IMU, EMG, optical sensors). You will be part of our interdisciplinary team of experts in artificial intelligence, human–computer interaction, computer vision, sensing, cognitive science, and UX design, that is defining the next era of human-centered computing. You will have access to Facebook’s cutting edge machine-learning resources and infrastructure, and test your models in real-time on prototype AR systems.

Responsibilities

• Design and build computer vision and multi-modal machine-learning models for real-time pose estimation and gesture recognition
• Collaborate with other research engineers and scientists to advance research in real-time computer vision methods for tracking, object detection, and action recognition
• Collaborate with other research engineers and scientists to advance research in real-time inference from multimodal data streams, including IMU, EMG, optical sensors, and cameras
• Train and evaluate models at small, medium, and large scales in a modern, parallelized ML environment (distributed clusters, multicore SMP, GPU)
  

Minimum Qualification

• MSc or PhD in the field of machine learning, computer science, signal processing, deep learning, artificial intelligence, or related technical field
• 3+ 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
• 3+ years of computer vision experience that provides familiarity with fundamental concepts such as image formation and camera calibration
• 3+ years of experience in at least one deep-learning software library (e.g., PyTorch, Caffe2, Tensorflow, Keras, Chainer) and at least one CV library such as OpenCV. This experience should include formulation, training, and evaluation of new algorithms and writing reusable modules
• 3+ years of experience developing end-to-end ML pipelines, including dataset preprocessing, model development and evaluation, and software 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
  

Preferred Qualification

• Experience designing data-collection protocols and recording datasets for machine-learning systems
• Experience with sensor systems and joint hardware/algorithm design, in particular with camera hardware
• Experience with building machine learning systems that leverage wristband sensors
• Experience with hand or body tracking, state-of-the-art machine-learning models for time-series modelling (e.g. inertial, audio, video), and human-computer interaction
• Track record in developing novel state-of-the-art machine learning systems and algorithms within a research environment
  

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.