Sr. Software Engineer - AI BioDesign at Allen Institute in Seattle

Job description

• The Allen Institute accelerates science for a healthier world through large-scale research designed to answer some of the most complex questions in biology. Our multi-disciplinary teams generate foundational knowledge, tools, and data to understand how our brain, cells, and immune system work. We share our work openly so others can build on it, move faster, and ask bigger questions. We drive discovery forward and create new possibilities for improving human health.
• The AI BioDesign research collaboration has a bold vision to make biology engineerable by combining AI and high-throughput experimentation to predict, understand, and design living systems. Our scientific teams address high-risk, high-reward questions in biology through AI – inventing computational methods and large-scale AI/ML models that turn complex biological data into scientific insight. This work spans collaborations across Allen Institute Accelerators, including Brain Science, Cell Science, Immunology, Neural Dynamics, and the Seattle Hub for Synthetic Biology, as well as external academic and institutional partners.
• We are searching for a talented and enthusiastic Sr. Software Engineer to manage the data, data science, and ML training stacks across multiple flywheels. As a member of our close, collaborative team, you will have the freedom to contribute to as much of our code and design processes as you would like. In addition, you can train and develop novel models alongside our AI scientists, based on your interests and skills.
• 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.

Responsibilities

• Build and maintain ML training and evaluation pipelines for ML models across multiple biological modalities
• Design data storage, versioning, and access infrastructure for large-scale, in-house data
• Develop and maintain a model zoo of relevant models
• Working with the director to make/build versus buy decisions on training and data technical stack
• Develop processes to support a lab-in-the-loop training paradigm
• 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.

Requirements

• A bachelor's degree; or equivalent combination of education and experience
• 5 years of relevant experience
• Experience running/evaluating ML models and building data access APIs
• Familiarity with build processes and CI, such as GitHub Actions
• Experience deploying AI models in biological or scientific settings
• Experience making build versus buy technical decisions
• Some experience optimizing models for inference
• Some experience debugging ML training pipelines

Skills

Required

• Experience running/evaluating ML models
• Building data access APIs

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.
• $167,850 - $209,750 *
• * Final salary depends on the required education for the role, experience, level of skills relevant to the role, and work location, where applicable.