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AI System Infrastructure and MLOps Engineering Manager
2 months ago
We are seeking a highly skilled and experienced Manager of AI System Infrastructure and MLOps Engineering to join our team at Promote Project. As a key member of our AI/ML and Data Engineering team, you will be responsible for the stability and scalable operations of our leading-edge GPU Cloud Compute Cluster.
This role will involve guiding our AI Systems Infrastructure and MLOps efforts focused on our GPU Cloud Cluster operations, ensuring that our systems are highly utilized, performant, and stable. You will work in collaboration with other members of our AI Engineering team as well as the Science Initiative's AI Research team as they iterate and train their deep learning code, optimizing systems operations and helping to troubleshoot problems encountered by jobs running on the cluster.
Key Responsibilities- Build out the MLOps and Systems Infrastructure Engineering team to support large-scale capacity systems and AI training efforts.
- Drive MLOps processes and System Infrastructure Engineering efforts to ensure our GPU Cloud computing systems are highly utilized and stable.
- Own the on-call efforts for our GPU Cloud computing systems, building out the MLOps and Systems Infrastructure Engineering alerting and monitoring efforts for our leading-edge Kubernetes-based AI platform.
- Responsibility for AI/ML development infrastructure, instrumentation, and telemetry projects that empower our team in supporting our users across the AI/ML lifecycle.
- Mentor and manage your team in fulfilling their roles to the best of their abilities, providing skill and career coaching to help team members grow along their own career and life paths.
- Hands-on AI/ML Model Training Platform Operations experience in an environment with challenging data and systems platform challenges.
- MLOps experience working with medium to large-scale GPU clusters in Kubernetes, HPC environments, or large-scale Cloud-based ML deployments (Kubernetes preferred).
- BS, MS, or PhD degree in Computer Science or a related technical discipline or equivalent experience.
- 2+ years of experience managing MLOps teams.
- 7+ years of relevant coding and systems experience.
- 7+ years of systems Architecture and Design experience, with a broad range of experience across Data, AI/ML, Core Infrastructure, and Security Engineering.
- Strong understanding of scaling containerized applications on Kubernetes or Mesos, including solid understanding of AI/ML training with containers using secure AMIs and continuous deployment systems that integrate with Kubernetes or Mesos (Kubernetes preferred).
- Proficiency with Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure, and experience with On-Prem and Colocation Service hosting environments.
- Solid coding ability with a systems language such as Rust, C/C++, C#, Go, Java, or Scala.
- Extensive experience with a scripting language such as Python, PHP, or Ruby (Python preferred).
- Working knowledge of Nvidia CUDA and AI/ML custom libraries.
- Knowledge of Linux systems optimization and administration.
- Understanding of Data Engineering, Data Governance, Data Infrastructure, and AI/ML execution platforms.
- PyTorch, Karas, or Tensorflow experience a strong nice to have.
We offer a competitive salary range of $214,000 - $321,000, depending on location and experience. We also provide a comprehensive benefits package, including 100% match on employee 401(k) contributions, annual funding for employees, and relocation support for employees who need assistance moving to the Bay Area.
We believe that the strongest teams and best thinking are defined by the diversity of voices at the table. We are committed to fair treatment and equal access to opportunity for all CZI team members and to maintaining a workplace where everyone feels welcomed, respected, supported, and valued.
