Senior Specialist, Computational Protein Design

Merck • South San Francisco, CA

11d • $144,800 - $227,900

About The Position

We are seeking an innovative and experienced computational protein design scientist to join the Discovery Biologics Protein Engineering department. In this role, you will lead AI- and structure-guided protein design efforts, driving iterative design cycles from concept to candidate. As a functional subject matter expert, you will interface across Discovery Biologics, computational biology, and therapeutic area teams to shape and execute our AI-enabled protein design strategy. We recognize that our team is our strength and are committed to creating an inclusive environment for all employees. Successful candidates must demonstrate inclusive behaviors in working with a group of scientists to drive our core mission.

Requirements

• Hands-on experience with modern protein design tools (e.g., AlphaFold, Rosetta, RFDiffusion, ProteinMPNN, ESM, or equivalent), including generative models, model training, fine-tuning, large-scale inference, and performance evaluation in a research setting
• Proven ability to develop and benchmark computational pipelines for large-scale candidate generation and design library creation
• Strong protein biophysics intuition with a proven track record of optimizing expression, stability, affinity, and developability, and translating structural and biophysical insights into experimentally validated design outcomes
• Demonstrated track record through high-impact publications, conference presentations, or open-source contributions in computational protein design or a closely related field
• Excellent verbal and written communication and collaboration abilities

Nice To Haves

• Deep understanding of protein biophysics and structure–function relationships, with the ability to quickly contextualize and adapt design strategies to new targets
• Expertise in functional optimization of biologics, especially antibodies
• Demonstrated proficiency in computational protein design method/algorithm development
• Prior hands-on wet lab protein engineering experience

Responsibilities

• Familiar with the state-of-the-art generative models (e.g., RFDiffusion, ProteinMPNN, ESM3) and apply these protein design methods within iterative design–test–learn cycles; benchmark approaches against experimental outcomes to guide strategy.
• Apply physics-based and ML protein design tools (e.g., Rosetta, AlphaFold2), integrating structural and biophysical intuition to drive functional optimization of biologics, including antibodies, VHHs, bispecifics, and scFvs.
• Build AI-powered iterative design cycles that integrate high-throughput screening data and predictive models to improve hit rates, candidate quality, and speed to progression.
• Build computational workflows that further program goals, leveraging existing HPC/cloud resources and partnering with other of our company's Research Laboratories teams as needed.

Benefits

• medical, dental, vision healthcare and other insurance benefits (for employee and family)
• retirement benefits, including 401(k)
• paid holidays
• vacation
• compassionate and sick days

What This Job Offers

• Job Type: Full-time
• Career Level: Senior