About Arc Institute

The Arc Institute is a new scientific institution that conducts curiosity-driven basic science and technology development to understand and treat complex human diseases. Headquartered in Palo Alto, California, Arc is an independent research organization founded on the belief that many important research programs will be enabled by new institutional models. Arc operates in partnership with Stanford University, UCSF, and UC Berkeley.

While the prevailing university research model has yielded many tremendous successes, we believe in the importance of institutional experimentation as a way to make progress. These include:

  • Funding: Arc will fully fund Core Investigator’s (PI’s) research groups, liberating scientists from the typical constraints of project-based external grants.
  • Technology: Biomedical research has become increasingly dependent on complex tooling. Arc Technology Centers develop, optimize and deploy rapidly advancing experimental and computational technologies in collaboration with Core Investigators. 
  • Support: Arc aims to provide first-class support—operationally, financially and scientifically—that will enable scientists to pursue long-term high risk, high reward research that can meaningfully advance progress in disease cures, including neurodegeneration, cancer, and immune dysfunction.

Arc scaled to nearly 100 people in its first year. With $650M+ in committed funding and a state of the art new lab facility in Palo Alto, Arc will continue to grow quickly to several hundred in the coming years.

About the position

As Arc’s Infrastructure Engineering Manager, you will build, deploy, and maintain computing systems that enable cutting edge scientific research. You’ll collaborate closely with our Core Investigators and Tech Centers, apply your expertise, and manage key vendors, consultants, and cloud providers to ensure that Arc has world class infrastructure. This is an opportunity to build the infrastructure technology stack from the ground up for sophisticated users. This is an individual contributor role with potential to grow and manage a small team over time. Some examples of the kinds of work you will own and build:

  • Large scale data processing workflows that synchronize across on-prem and cloud environments 

  • Scheduled and on-demand GPU-accelerated workloads for ML training and validation

  • Data ingestion and pipelines from scientific instruments to storage and analysis

  • Data lake/warehousing/cold storage

  • Analytics tooling and reporting

  • User access and management

  • Comprehensive metrics, monitoring, and alerting to ensure our infrastructure is highly available and scalable

About you

  • You love to build. Whether it’s new infrastructure from scratch or adding capabilities to a large-scale operation, you enjoy the work to define and execute on a new project instead of just maintaining it.

  • You are a collaborator. You like building relationships as much as writing code. You’ve experienced the super power of great teamwork and seek out opportunities to create with colleagues.

  • You care about more than the tech stack. You know the tools and frameworks, but you like to understand the why and the who, the purpose behind the system, and the people who are going to use it.

  • You think strategically. You believe that high quality results come from a clear plan. You like looking weeks, months, or years ahead to make sure you’re building the right thing for the long term.

  • You are inspired by science. Whether you have worked in biotech or barely know what CRISPR is, you see the transformational potential of computational biology, and want to contribute to advancing the field with your expertise.

In this position you will

  • Develop a comprehensive strategy, roadmap, and budget for computational infrastructure at Arc that meets current and future needs

  • Learn or build on an understanding of the research, data, and computational use cases in Arc’s focus areas

  • Collaborate closely with Arc’s science and operations teams to enable world class research and results

  • Build and deploy on-prem, cloud, and orchestration resources that efficiently and effectively support our research paths

  • Ensure the scalability, reliability, and security of our infrastructure and applications

  • Collaborate with other Operations teams to set goals, build teams, problem solve, and develop a unique culture

  • Manage vendors and consultants who contribute to Arc’s infrastructure needs

Requirements

  • A Bachelor's degree in computer science or related fields; master’s degree preferred

  • 8+ years experience building infrastructure for machine learning and/or other intensive computing applications; some exposure to life sciences preferred

  • Familiarity with major cloud provider capabilities such as GCP and AWS

  • Experience with GPU compute frameworks such as CUDA, job schedulers such as LSF/Slurm, and other infrastructure relevant technologies such as Python and Linux

  • Exposure to key hardware components such as storage arrays, databases, on-prem CPU and CPU based compute clusters, gigabit ethernet, and other real world infrastructure

  • Previous experience managing on-prem and cloud infrastructure at large scale

  • Exceptionally strong communication and information synthesis skills

  • Experience working in a fast paced startup environment with high levels of collaboration and many inputs

  • Skilled influencer with ability to form strong relationships across all levels and functions at Arc

  • Excellent problem solving and analytical skills with the ability to design solutions in an ambiguous environment

  • Bias for action with ability to lead both tactically and strategically

  • Demonstrated ability to build programs, processes, and metrics in a scaling organization

  • A little humor

The base salary range for this position is $168,500 - $211,500. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, internal equity, market conditions, education/training, and skill level, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

 

 

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