Meta AR/VR Job | Codec Avatars Large Scale Experimentation Research Engineer
Type（岗位类型）: 3D Software Engineering
Citys（岗位城市）: Pittsburgh, PA
Meta Reality Lab’s Codec Avatar Research team is building technology to enable immersive, photorealistic social presence. Codec Avatars are real-time live-drivable representations that match the appearance of their users. As part of the Lab’s Instant Codec Avatar group, you’ll work to scale up Codec Avatar technology by modeling the diversity of human appearance and applying that model to the process of rapidly generating new avatars.
This role is focused on our Large Scale Experimentation work, which both supports our new Research Supercluster compute resource and uses that resource to run large-scale machine learning experiments that advance the state-of-the-art in Codec Avatar technology. In this role, you will join a team of software engineers, research engineers, and research scientists to deliver software systems needed to support large scale model training over thousands of GPUs. These systems ingest, store, and serve some of the largest ML training datasets in the world, and coordinate complex workflows composed from a mixture of traditional graphics and ML algorithms. You’ll also design, execute, and analyze research experiments using those workflows to advance our understanding of how appearance modeling scales over large populations.
Experience developing and debugging distributed systems
Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
Effective communication skills, including experience driving decision making
Quantitative reasoning skills to analyze trade offs of different hardware and software solutions
Masters or higher degree in Computer Science or related technical field, or equivalent experience.
Experience working with cross functional teams including hardware, software, network, legal, privacy and security
Proven Linux/shell scripting development experience
Experience developing reliable multi-stage data pipelines
Develop and debug machine learning workflows on a large multi-node cluster.
Automation of data ingress into cluster
Implement compute allocation policy for the cluster
Define and implement strategy for compute environment management and deployment
Define and communicate cluster software requirements, based on research needs
Enabling adoption of the cluster by additional research cases
Definition, design and implementation of automated testing
Point of contact for hardware & software questions regarding cluster capabilities
Reporting on progress, presenting technical risks, challenges and status to executive management.
Partner with Data Collection and Asset Generation teams to specify and ingest assets required for large scale training.
Partner with Codec Avatars Universal Avatar Research team to support large scale experimentation based on python workflows.
Partner with Research SuperCluster production engineering team to support reliable operation.
Partner with Research SuperCluster storage engineering team to support development of features required for Codec Avatars datasets
Partner with security, privacy, and policy teams to ensure workflow compliance with company policy.
Experience with containers (Docker or similar)
8+ years of experience
Experience developing or applying computer graphics algorithms
5+ years of experience developing workflows for large scale AI training
Experience developing or applying computer vision algorithms
Experience operating in a self-directed environment with multiple stakeholders across multiple teams
Understanding of deep neural network training
Experience with securing sensitive data (encryption, access control, audit logging)
Experience with HPC (High Performance Computing)
Experience with scheduling systems such as Slurm or Kubernetes
Large scale object storage services (S3 or similar)
Experience in research or converting research to products