Senior AI Peptide and Protein Design Engineer

AllSTEM Connections is seeking a Senior AI Peptide and Protein Design Engineer to work onsite in Los Angeles, CA.

This is a full-time, direct hire opportunity.

Annual Base Salary: DOE, $160,000-$213,000 along with bonus eligibility and a comprehensive benefits package.

M-F, 8AM - 5PM.

SUMMARY:

Our confidential client, a prominent research institute, is launching a strategic new initiative in de novo peptide and protein engineering to advance the design and delivery of next-generation therapeutics. This effort represents a deliberate expansion of the organization’s capabilities and will establish a strong foundation in AI-driven peptide and protein engineering.

The successful candidate will play a central role in shaping core tools, workflows, and technical direction, while working closely with experts in peptide and protein design who are deeply engaged in the program. The Senior AI Peptide and Protein Design Engineer role offers the opportunity to influence the initiative from its inception with strong scientific partnership and institutional support. Candidates with strong peptide and protein design backgrounds are encouraged to apply.

Why You Should Join Us:

• Build a Foundational Capability: Help establish and scale core AI-driven peptide and protein engineering capabilities from the ground up.
• Translational Focus: Work on technologies designed to directly influence therapeutic discovery and development across multiple programs.
• Cross-Functional Collaboration: Work in a highly integrated environment with physicians, computational scientists, peptide and protein characterization and experimental teams to translate designs from concept to therapeutic candidates.
• High Ownership and Impact: Shape tools, workflows, and technical direction with visibility across research and leadership.

RESPONSIBILITIES:

• De Novo Design Pipelines: Develop, deploy, and continuously improve computational pipelines for de novo peptide and protein design, including property prediction using data-driven and modeling approaches. Define robust benchmarking, performance metrics, and validation strategies.
• Peptide and Protein Design: Design and optimize novel peptide and protein therapeutics using sequence- and structure-based computational design methods, leveraging silico predictions to support lead identification and optimization.
• Design-Build-Test Cycles: Work directly with the peptide and protein production and characterization teams to experimentally test designs, interpret results, and incorporate feedback into iterative design cycles.
• Cross-Functional Integration: Collaborate with target biology and translational research teams to evaluate designs in biological context and support progression from concept to optimized lead candidates.
• Mentorship: Mentoring junior scientists or contributing to hiring and team growth.
• Documentation & Communication: Maintain clear, reproducible documentation of methodologies, code, and results. Communicate findings effectively to scientific and leadership stakeholders.
• Culture & Leadership: Contribute to a high-performing scientific culture that values rigor, innovation, transparency, collaboration, accountability, and efficient execution.

QUALIFICATIONS:

• Ph.D. in Computational Peptide/Protein Design, Structural Biology, Protein Engineering, or a closely related field.
• Postdoctoral or industry experience applying computational modeling to peptide or protein engineering, and a strong publication record or proven track record contributing to therapeutic development.
• 5 years of hands-on experience in peptide and protein design, modeling, and sequence/structure-function prediction, with proficiency in relevant. macromolecular modeling software (i.e. AlphaFold, RoseTTAFold, RFdiffusion, RFpeptides, Boltz, ProteinMPNN).
• Demonstrated understanding of peptide and protein biology, including structure, folding, stability, and experimental constraints, gained through direct experimental work and/or close collaboration with wet-lab teams.
• Strong analytical and problem-solving skills applied to complex biological and computational challenges.
• Excellent teamwork, time management, documentation, and communication skills
• Proven ability to work effectively in interdisciplinary, cross-functional research environments.