Senior Scientist — AI-Driven Protein Design & Pipelines

BioSpace; South San Francisco (CA); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Discretionary annual bonus

Stock-based long-term incentives

Flexible work models

Retirement and Savings Plan

Job summary

Amgen in South San Francisco is seeking a Senior Scientist - Computational Protein Design to develop and deploy automated computational pipelines for large-scale binder design, supporting discovery by generating molecules for novel biology.

You will design and prioritize binders, build scalable pipelines for de novo proteins, collaborate with experimental teams, and contribute to shared tools while applying AI/ML methods.

Qualifications

• Doctoral degree or equivalent in a relevant field.
• Masters degree with 3 years of protein design experience
• Bachelor's degree with 5 years of protein design experience

Responsibilities

• Develop and automate ML protein design workflows for binder generation
• Build scalable pipelines for designing large libraries of de novo proteins across multiple targets
• Apply computational methods to support multiplexed screening strategies and receptor discovery efforts
• Design and prioritize binders for individual targets and large target panels
• Collaborate with experimental scientists and data teams to enable rapid validation and iteration

Skills

Python programming

ML workflows

Protein design

C++/scripting

Education

PhD in a relevant field

MD or PharmD or equivalent

Master's degree + 3 years protein design

Bachelor's degree + 5 years protein design

Tools

Python

AlphaFold

ProteinMPNN

RFdiffusion

Cloud computing/HPC

Job description

Amgen in South San Francisco is seeking a Senior Scientist - Computational Protein Design to develop and deploy automated computational pipelines for large-scale binder design, supporting discovery by generating molecules for novel biology.

You will design and prioritize binders, build scalable pipelines for de novo proteins, collaborate with experimental teams, and contribute to shared tools while applying AI/ML methods.