AI Acceleration Software Development Lead
6 days ago
Meta is a leader in the AI and machine learning space, dedicated to developing innovative technologies that transform the way people interact with each other. Our team focuses on creating high-performance software and hardware technologies for AI at datacenter scale.
Salary Range: $177,000/year to $251,000/year + bonus + equity + benefits
About the Role
The MTIA (Meta Training & Inference Accelerator) software team is responsible for exploring, developing, and productizing high-performance software and hardware technologies for AI at datacenter scale. As part of this team, you will be working on the development of PyTorch compiler frontend for MTIA, PyTorch runtime for inference & training, high performance kernel libraries exploiting various hardware architectural features and tooling.
We are seeking an experienced engineering manager to support MTIA software stack development for inference and training platform. The ideal candidate will have a strong background in software engineering, leadership, and communication skills. They should be able to manage a diverse team of developers, help them develop their careers, and assign projects tailored to their skill levels.
Responsibilities
- Manage a team of domain experts developing AI acceleration software stack for MTIA
- Operate strategically and tactically to develop the vision and strategy for the team, while managing day-to-day software development
- Communicate and collaborate effectively with peer engineering teams
- Work closely with dedicated recruiting staff to expand the team, including sourcing candidates, interviewing candidates, and on-boarding new employees
Requirements
- At least 2 years of experience in managing a software team in a fast-paced capacity
- Demonstrated experience recruiting, building, structuring, leading technical organizations, including performance management
- Experience developing AI inference and/or training software stack
- Strong understanding of deep learning frameworks such as PyTorch, TensorFlow, JAX, ONNX, MXNet, TensorRT etc
- Knowledge of deep learning models such as recommendation, ranking, LLM etc
- Familiarity with AI hardware such as GPUs, deep learning accelerators is a plus
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