ML Engineer

Contract: 12 Months+

Request Highlights:

• Team: AI and Systems Co-Design, Accelerator Enablement
• Key projects: Large language model (LLM) inference performance improvements evaluations and performance benchmarking
• MTIA inference accelerator dev efficiency
• Purpose of team: Develop highly efficient training and inference systems customized to Meta AI workloads at scale
• Reason for request: Dev efficiency improvements
• Candidate will get to work on state-of-the-art large ML infrastructure that empowers production large language models and content recommendation models deployed
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Job Responsibilities:

• Develop highly scalable GPU machine learning training system and custom inference hardware solution for a variety of AI workloads
• Implement and evaluate state-of-the-art performance optimization for large scale training and inference systems
• Code deliverables with engineering team with potential opportunity for external publication

Requirements / you will develop:

• Great communication working with team to understand business context and project roadmap
• Good and concise end-to-end programming skill across ML platform stacks such as Caffe2, Pytorch
• Across the board understanding of distributed training algorithms, memory/compute efficiency optimization, and how they affect high-level product metrics

Must-Haves / Non-Negotiable Skills:

• Python, C++ programming fluency
• Experience with Pytorch programming
• Experience with system performance analysis

Good-to-Haves:

• Strong communication and collaboration skills
• Experience with GPU programming and performance optimization
• Experience with large-scale system development and performance characterization/optimization