Scientist III – Proteome Editor Design / AI BioDesign

Allen Institute; Seattle (WA); On-site; USD 128,000 - 160,000; Full time

Benefits offered by this job

Relocation assistance

Possible visa sponsorship

Job summary

The Allen Institute seeks a scientist to lead the Proteome Editor flywheel. This role focuses on cell‑based library screening and functional genomics to design de novo proteome editors that work out of the box.

You will partner with machine learning colleagues to optimize active‑learning strategies, improve turnaround time, and deliver model‑ready datasets while mentoring a high‑performing team onsite in Seattle.

Qualifications

• PhD or equivalent in biochemistry, molecular biology, or related field.
• Minimum 5 years of post‑doctoral experience.
• Experience with functional genomics, MPRA, and high‑throughput screening.
• Proven ability to lead projects and collaborate cross‑functionally with ML teams.

Responsibilities

• Lead the Proteome Editor flywheel team to design‑test‑learn pipelines.
• Oversee library screening and degrader evaluation experiments.
• Collaborate with ML colleagues to define targets and curate data.
• Improve turnaround time, throughput, and model lift.

Skills

Functional genomics

MPRAs

Multiplexed assays

High-throughput screening

Collaboration with ML teammates

Education

PhD in biochemistry or molecular biology

Tools

CRISPR/Cas9 editing

Golden Gate assembly

Gibson assembly

NGS library prep

Mammalian cell culture

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.

Join AI BioDesign, an initiative to make biology engineerable by combining AI and high-throughput experimentation. Join us as we build a series of interconnected design-test-loop “flywheels” that enable design of synthetic enhancers, protein binders, and more.

We’re seeking a scientist to lead our proteome editor flywheel. The proteome editor flywheel team is part of a larger effort that includes a total of three experimental flywheel teams and one machine learning team. The goal of the proteome editor flywheel is to produce a model that can design de novo proteome editors that work out of the box. For more information on the concept of a proteome editor, see https://pmc.ncbi.nlm.nih.gov/articles/PMC12632987/ — a recent publication on “degraders,” which are the proteome editors that will be our focus.

To lead this flywheel team, you will need a strong background in cell-based library screening, functional genomics, or synthetic cellular biology. You will lead your team and interact with other team leads, including machine learning colleagues, to optimize active learning processes in your flywheel. You will optimize your flywheel’s turn‑around‑time and per‑cycle model improvement, racing to deliver the best possible ML models for proteome editor design. You will need a high degree of emotional intelligence, a collaborative mindset, and an ability to work cross‑functionally with other research teams to drive project success.

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

• Lead the Proteome Editor team to build and run a rapid, repeatable design–test–learn pipeline focused on proteome editor screening
• Design and oversee library screening and degrader evaluation experiments to generate high-quality, model‑ready datasets
• Partner with machine learning colleagues to define next targets, curate data, and implement active‑learning strategies that choose the next best experiments
• Optimize flywheel performance by improving turnaround time, throughput, cost, and per‑cycle model lift; identify and remove experimental bottlenecks
• Coordinate closely with other flywheel leads and AI Biodesign stakeholders to align priorities, timelines, and dependencies across the broader program
• Mentor and manage a high‑performing team, fostering a collaborative culture and clear communication grounded in strong emotional intelligence
• Present scientific results and complex concepts internally in talks and progress reports
• Present results to the external community at conferences and in publications

Required Experience And Education

• PhD degree in biochemistry, molecular biology, or a related field; or equivalent combination of degree and experience
• Minimum 5 years of relevant post‑doctoral experience
• Experience with functional genomics, massively parallel reporter assays, multiplexed assays of variant effect, saturation mutagenesis, or plasmid library‑based screening
• Experience architecting cellular library screening workflows (e.g., MPRAs or other high‑throughput cell‑based discovery platforms)
• Proven ability to lead scientific projects and collaborate cross‑functionally, including partnering effectively with computational/ML teammates

Preferred Education And Experience

• 5 – 8 years relevant post‑doctoral experience
• Experience designing or optimizing cell‑based synthetic effectors
• Experience building or operating data‑driven/active‑learning experimental loops and translating assay outputs into model‑ready datasets
• Experience with protein engineering/interaction prediction approaches and modern analysis pipelines (e.g., sequence‑to‑function modeling, structural modeling, or high‑throughput data QC/processing)
• Experience performing molecular biology methods including library cloning, Golden Gate assembly, Gibson assembly, CRISPR/Cas9‑editing, mammalian cell culture, stem cell culture, and NGS library prep

Physical Demands

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

Work Environment

• Frequently required to sit, stand, walk, stoop, kneel or reach
• Possible exposure and handling of laboratory animals
• Laboratory atmosphere - possible exposure to chemical, biological or other hazardous substances

Position Type/Expected Hours of Work

• This role is currently working onsite and is expected to work onsite for the majority of the working hours. We are a Washington State employer, and the primary work location for Allen Institute employees is 700 Dexter Ave N.; any remote work must be performed in Washington State

Travel

• The successful candidate may be invited to attend occasional national and international conferences

Additional Comments

• **Please note, this opportunity offers relocation assistance**
• **Please note, this opportunity may offer work visa sponsorship**

Annualized Salary Range

• $128,050 - $160,050
• Final salary depends on required education for the role, experience, and level of skills relevant to the role, along with 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.