Postdoc Research Scientist, Systems ML (PhD) - Meta

Meta Reality Labs Research (RLR) is dedicated to the research and development required to bring virtual and augmented reality to billions of people around the world. At our lab, we aspire to a vision of social VR and AR, where people are able to interact with each other across distances in a way that is indistinguishable from in-person interactions. RLR is looking for a talented postdoc research scientist to research on compute solutions for accelerating the progression to authentic social presence in virtual reality with hardware and software codesign. In our current pipeline, a multitude of sensing components, including image sensors, microphones, and inertial measurement units are installed on the headset prototypes in order to collect a rich suite of information that reflects the user's physical state, with an emphasis on modality synchronicity and latency minimization; this information is then processed by our state-of-the-art algorithms running on existing SoC platform or custom energy efficient silicon to allow for a computational representation of the user. Individuals in this role are expected to be recognized experts in identified research areas such as computer architecture, machine learning, and edge computing, particularly including areas such as neural network (NN) accelerator modeling and design, neural network architecture search (NAS), parallel computing, and compiler design and optimization. The ideal candidate will have a keen interest in producing creative compute architecture to make authentic social presence more energy efficient while running at real-time. You will work in a dynamic cross-functional team including research scientists, silicon experts and software engineers, as well as platform design and quality evaluation experts. Strong communication and interpersonal skills are required.This Postdoctoral position is for 24 months.

RESPONSIBILITIES

Postdoc Research Scientist, Systems ML (PhD) Responsibilities:

• Lead research to advance the science and technology of computer architecture and hardware-software codesign
• Lead research that enables the best hardware efficiency for deep learning models
• Design better NN quantization and hardware aware NAS algorithms
• Collaborate on research within RLR team
• Influence progress of relevant research communities by producing publications

MINIMUM QUALIFICATIONS

Minimum Qualifications:

• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Ph.D. degree in Electrical Engineering, Computer Engineering, Computer science, or equivalent
• Publications in accelerator design, machine learning, AI, NAS, NN quantization, or related technical fields
• Experience in one or more of the following areas: Deep Learning, AI Infrastructure, Machine Learning Accelerators, High Performance Computing, Machine Learning Compilers, mobile GPU Architecture, Machine Learning Frameworks, and On-Device Optimization
• Experience in theoretical and empirical research for addressing research problems
• Experience in communicating research for public audiences of peers
• Knowledge in advanced programming languages, such as C/C++ and Python
• Familiar with embedded systems and mobile platform
• Familiar with cross platform compilation and Linux application development
• Experience with frameworks like PyTorch, Caffe2, TensorFlow, ONNX, and TensorRT
• Knowledge on Image processing, computer vision, and or computer graphics
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment

PREFERRED QUALIFICATIONS

Preferred Qualifications:

• Experience holding a faculty, industry, or government researcher position
• 1+ year(s) of work experience in a university, industry, or government lab(s), in a role with primary emphasis on heterogeneous computing research for AI acceleration
• First-author publications at peer-reviewed AI conferences (e.g. DAC, ISCA, MICRO, NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL)
• Experience with accelerator modeling with HW/SW codesign for CV or graphics applications
• Experience in driving original scholarship in collaboration with a team
• Experience with realtime optimization for product features or real applications on edge devices