Allen Institute

Software Engineer III – AI/ML Infrastructure, Biology

Allen Institute

full-time

Posted on:

Origin:  • 🇺🇸 United States • Washington

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Salary

💰 $144,450 - $180,550 per year

Job Level

JuniorMid-Level

Tech Stack

AWSAzureCloudGoogle Cloud Platform

About the role

  • Assist the development of state-of-the-art engineering infrastructure at the Allen Institute to support AI/ML research and applications Enable data management, software infrastructure and AI/ML workflow best practices and policies Build tooling to enable model development and scale across many GPUs and across multiple clouds Collaborate with teams of scientists, computational biologists, PMs, UX researchers and software engineers within the Allen Institute and external partners Help establish community standards for scalability in developing, disseminating, and evaluating AI/ML/computational methods for scientific problems Participate in institute-wide initiatives, workshops, and seminars to promote engineering excellence through technical leadership, cross-disciplinary collaboration and knowledge sharing Note: Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This description reflects managements assignment of essential functions; it does not proscribe or restrict the tasks that may be assigned.

Requirements

  • Bachelors Degree in Computer Science or related technical field or equivalent experience 2-5 years of experience working with MLOps in medium to large scale GPU clusters and/or cloud based ML deployments Experience with building, deploying and maintaining machine learning models Proficiency with cloud computing (AWS, GCP or Azure) and with on-prem clusters Experience with databases, large data management Working knowledge of AI/ML custom libraries, AI/ML execution platforms Proven ability to work independently and manage multiple projects simultaneously while meeting deadlines Excellent written and verbal communication skills, with the ability to collaborate effectively in a multidisciplinary team environment