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.

Facebook Reality Labs brings together a world-class team of researchers, developers, and engineers to create the future of virtual and augmented reality, which together will become as universal and essential as smartphones and personal computers are today. And just as personal computers have done over the past 45 years, AR and VR will ultimately change everything about how we work, play, and connect.We are developing all the technologies needed to enable breakthrough AR glasses and VR headsets, including optics and displays, computer vision, audio, graphics, brain-computer interface, haptic interaction, eye/hand/face/body tracking, perception science, and true telepresence. Some of those breakthroughs will advance much faster than others, but they all need to happen to enable AR and VR that are so compelling that they become an integral part of our lives. The audio team at Facebook Reality Labs Research is looking for experts in machine learning and computer vision. This role is focused in design, development and engineering of advanced computer vision systems that drive audio visual experiences design and synthesis in AR and VR. An ideal candidate will be passionate about the development of advanced proof-of-concept demonstration platforms and about pushing the state of the art by conducting fundamental research. The position is full-time and requires a PhD in computer science, deep learning, machine learning, computer vision, computer engineering or statistics.

Responsibilities

• Independently implement state-of-the-art models and techniques on PyTorch, TensorFlow or other platforms.
• Independently identify, motivate, and execute on medium to large hypotheses (each with many tasks) for model improvements through data analysis, and domain knowledge, and are able to communicate your learnings effectively.
• Design, perform, and analyze online and offline experiments with specific and well thought-out hypotheses in mind.
• Generate reliable, correct training data with great attention to detail.
• Identify and debug common issues in training machine learning models such as overfitting/underfitting, leakage, offline/online inconsistency independently and consistently.
• Understand the model architecture used, and the consequences of this for different hypotheses tested. In general, you have a good understanding of computer vision from an applied perspective, even though you may not be up to date with the state-of-the-art.
  

Minimum Qualification

• Currently has, or is in the process of obtaining a PhD in the field of Deep learning, Machine Learning, Computer Vision, Computer Science, Computer Engineering or Statistics or a related field.
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
• 4+ years experience with development and implementation of computer vision or deep learning algorithms.
• 3+ years experience with scientific programming languages such as Python, C++, or similar.
• 1+ years experience implementing models and techniques on PyTorch, TensorFlow, or similar.
• 1+ years experience in implementing and evaluating work and end-to-end prototypical learning systems.
• Interpersonal skills: cross-group and cross-culture collaboration.
  

Preferred Qualification

• Experience with audio signal processing, audio-visual learning or similar.
• Experience with building models on acoustic datasets.
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as CVPR, ECCV/ICCV, or similar.
  

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.