Software Engineer III - AI/ML Infrastructure in Biology at Allen Institute

SW Engineer III - AI/ML Infrastructure in Biology

The mission of the Allen Institute is to unlock the complexities of bioscience and advance our knowledge to improve human health. Using an open science, multi-scale, team-oriented approach, the Allen Institute focuses on accelerating foundational research, developing standards and models, and cultivating new ideas to make a broad, transformational impact on science.

The mission of the Office of the Chief Technology Officer (CTO) is not only to provide state of the art engineering infrastructure to the Allen Institute as a whole, but to also address high-risk, high-reward questions in biology through AI.

We are seeking an independent and motivated Machine Learning (ML) engineer in the Office of the CTO AI Applications group. This position will work closely with AI researchers, scientists and engineering teams to build large AI/ML models for Biology and the computational infrastructure to support these models. The role is also expected to work collaboratively across all the Allen Institute teams including Brain Science, Cell Science, Immunology, Neural Dynamics, and the Seattle Hub for Synthetic Biology.

At the Allen Institute, we believe that science is for everyone � and should be open to everyone. We are dedicated to combating biases and reducing barriers to STEM careers more broadly.

We also believe that science is better when it includes different perspectives and voices. We strive to make the Allen Institute a place where everyone feels like they belong and are empowered to do their best work in a supportive environment.

We are an equal-opportunity employer and strongly encourage people from all backgrounds to apply for our open positions.

Essential Functions

• 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 management�s assignment of essential functions; it does not proscribe or restrict the tasks that may be assigned.

Required Education and Experience

• Bachelor�s 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

Preferred Education and Experience

• 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

Physical Demands

• Fine motor movements in fingers/hands to operate computers and other office equipment

Position Type/Expected Hours of Work

• This role is currently able to work both remotely and onsite in a hybrid work environment. We are a Washington State employer, and the primary work location for all Allen Institute employees is 615 Westlake Ave N.; any remote work must be performed in Washington State.

Travel

• Attendance and participation in national and international conferences as appropriate

Additional Comments

• **Please note, this opportunity does not offer relocation assistance**
• **Please note, this opportunity does not offer work visa sponsorship**

Annualized Salary Range

$144,450 - $180,550

* Final salary depends on the required education for the role, experience, level of skills relevant to the role, and work location, where applicable.

Benefits

• Employees (and their families) are eligible to enroll in benefits per eligibility rules outlined in the Allen Institute�s Benefits Guide. These benefits include medical, dental, vision, and basic life insurance. Employees are also eligible to enroll in the Allen Institute�s 401k plan. Paid time off is also available as outlined in the Allen Institutes Benefits Guide. Details on the Allen Institute�s benefits offering are located at the following link to the Benefits Guide:?https://alleninstitute.org/careers/benefits.

It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities.