Chan Zuckerberg Initiative

Manager, AI System Infrastructure and MLOps Engineering

Redwood City, CA
USD 214k - 321k
Machine Learning Kubernetes Azure Rust Scala Python Ruby C++ Go Java PyTorch TensorFlow GCP PHP Deep Learning AWS C#
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Description

The Chan Zuckerberg Initiative was founded by Priscilla Chan and Mark Zuckerberg in 2015 to help solve some of society’s toughest challenges — from eradicating disease and improving education to addressing the needs of our local communities. Our mission is to build a more inclusive, just, and healthy future for everyone.

The Team

Across our work in Science, Education, and within our communities, we pair technology with grantmaking, impact investing, and collaboration to help accelerate the pace of progress toward our mission. Our Central Operations & Partners team provides the support needed to push this work forward. 

Central Operations & Partners consists of our Brand & Communications, Community, Facilities, Finance, Infrastructure/IT Operations/Business Systems, Initiative Operations, People, Real Estate/Workplace/Facilities/Security, Research & Learning, and Ventures teams. These teams provide the essential operations, services, and strategies needed to support CZI’s progress toward achieving its mission to build a better future for everyone.

The AI/ML Infrastructure team works on building shared tools and platforms to be used across the Chan Zuckerberg Initiative, partnering and supporting the work of an extensive group of Research Scientists, Data Scientists, AI Research Scientists, as well as a broad range of Engineers focusing on Education and Science domain problems. Members of the shared infrastructure engineering team have an impact on all of CZI's initiatives by enabling the technology solutions used by other engineering teams at CZI to scale.

The Opportunity

As a hands-on Manager of the AI System Infrastructure and MLOps Engineering team, you will be joining the AI/ML and Data Engineering team in CZI Central Tech, with the responsibility for the stability and scalable operations of our leading edge GPU Cloud Compute Cluster. This supports our AI Researchers in their development and training of state-of-the-art models in artificial intelligence and machine learning to solve important problems in the biomedical sciences aligned with CZI’s mission, contributing to greater understanding of human cell function.

As the Engineering Manager of the AI Infrastructure and MLOps Engineering team, you will be responsible for a variety of MLOps and AI development projects that empower our AI Researchers and help to accelerate Biomedical research across the whole of the AI lifecycle. You will guide 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 be working in collaboration with other members of our own 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 in helping to troubleshoot problems encountered by jobs running on the cluster.

What You'll Do

  • Help to build out the MLOPs and Systems Infrastructure Engineering team, growing the team to support the large scale capacity systems and AI training efforts we will be undertaking.
  • Drive our MLOps processes and System Infrastructure Engineering efforts in ensuring that our GPU Cloud computing systems are highly utilized and stable, and proactively guide our team in implementing the instrumentation and observability tooling integral to our AI Platform.
  • 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, including troubleshooting problems encountered on the GPU platform infrastructure and  with  jobs running on the cluster and computing systems.
  • Responsibility for a variety of AI/ML development infrastructure, instrumentation, and telemetry projects that empower our team in supporting our users across the  AI/ML lifecycle, taking a key role in simplifying and optimizing the systems and processes that are integral to our GPU Cloud Cluster operations - in an MLOps meets SRE kind of hybrid operations model.
  • Mentoring and managing your team in fulfilling their roles to the best of their abilities, provide skill and career coaching to help the team members keep growing along their own career and life paths, and keep the team engaged in meaningful and interesting projects in service of our north star philanthropic mission

What You'll Bring

  • 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 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

Compensation

The Redwood City, CA base pay range for this role is $214,000 - $321,000. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. Pay ranges outside Redwood City are adjusted based on cost of labor in each respective geographical market. Your recruiter can share more about the specific pay range for your location during the hiring process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

  • CZI provides a generous 100% match on employee 401(k) contributions to support planning for the future. 
  • Annual funding for employees that can be used most meaningfully for them and their families, such as housing, student loan repayment, childcare, commuter costs, or other life needs.
  • CZI Life of Service Gifts are awarded to employees to “live the mission” and support the causes closest to them.
  • Paid time off to volunteer at an organization of your choice. 
  • Funding for select family-forming benefits. 
  • Relocation support for employees who need assistance moving to the Bay Area
  • And more!

Commitment to Diversity

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. Learn about our diversity, equity, and inclusion efforts. 

If you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.

Explore our work modesbenefits, and interview process at www.chanzuckerberg.com/careers.

 #LI-Hybrid 

 

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