Staff Software Engineer

Description:

What you'll do:

• Implement cost effective and scalable solutions to allow ML engineers to scale their ML training and inference workloads on compute platforms like Kubernetes.
• Lead and contribute to key projects; rolling out GPU sharing via MIGs and MPS , intelligent resource management, capacity planning, fault tolerant training.
• Lead the technical strategy and set the multi-year roadmap for ML Training Infrastructure that includes ML Compute and ML Developer frameworks like PyTorch, Ray and Jupyter.
• Collaborate with internal clients, ML engineers, and data scientists to address their concerns regarding ML development velocity and enable the successful implementation of customer use cases.
• Forge strong partnerships with tech leaders in the Data and Infra organizations to develop a comprehensive technical roadmap that spans across multiple teams.
• Mentor engineers within the team and demonstrate technical leadership.

What we're looking for:

• 7+ years of experience in software engineering and machine learning, with a focus on building and maintaining ML infrastructure or Batch Compute infrastructure like YARN/Kubernetes/Mesos.
• Technical leadership experience, devising multi-quarter technical strategies and driving them to success.
• Strong understanding of High Performance Computing and/or and parallel computing.
• Ability to drive cross-team projects; Ability to understand our internal customers (ML practitioners and Data Scientists), their common usage patterns and pain points.
• Strong experience in Python and/or experience with other programming languages such as C++ and Java.
• Experience with GPU programming, containerization, orchestration technologies is a plus.
• Bonus point for experience working with cloud data processing technologies (Apache Spark, Ray, Dask, Flink, etc.) and ML frameworks such as PyTorch.