Deep Learning Engineer - Distributed Task-Based Backends

Job Description

Seeking experienced software professionals to help build distributed backends for Deep Learning frameworks like PyTorch, JAX, and TensorFlow.

Requirements

• BS, MS, or PhD degree in Computer Science, Electrical Engineering, or related field
• 5+ years of relevant industry experience or equivalent academic experience
• Proficiency in Python and C++ programming
• Strong background in parallel and distributed programming, preferably on GPUs
• Hands-on development skills using Machine Learning frameworks
• Understanding of Deep Learning training in distributed contexts
• Experience with deep-learning compiler stacks and GPU performance optimization

Responsibilities

• Develop extensions to popular Deep Learning frameworks
• Develop compiler optimizations and parallelization heuristics
• Develop tools for performance debugging of AI models
• Study and tune Deep Learning training workloads at large scale
• Support enterprise customers and partners to scale novel models
• Collaborate with Deep Learning software and hardware teams
• Contribute to the development of runtime systems for distributed GPU computing

Benefits

• Multiple relocation packages
• Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO)
• 8-week parental leave
• 9 Employee Resource Groups
• Annual bonus offering
• Flexible work arrangements
• Up to 6% 401K matching