Senior AI Peptide and Protein Design Engineer

Senior AI Peptide and Protein Design Engineer

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

Location:

Los Angeles, CA

Formerly known as the Ellison Institute of Technology Los Angeles, the Ellison Medical Institute strives to spark innovation, leverage technology, and drive interdisciplinary, patient-centered research to continually enhance health, reimagine and redefine cancer care, and transform lives. Established in 2016 as a medical research and development center, the Institute features innovation labs for artificial intelligence and molecular analytics and was among the first organizations to vertically integrate the interdisciplinary study and treatment of disease.

We offer multifaceted programs, including a preventative medicine and cancer clinic, cross-disciplinary research laboratories, a health policy think-tank, and community outreach and educational programs.

Job Summary The Ellison Medical 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.

• 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.

• 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.

• Required
  
  Education:
  
  Ph.D. in Computational Peptide/Protein Design, Structural Biology, Protein Engineering, or a closely related field.
• Required Experience:

• Postdoctoral or industry experience applying computational modeling to peptide or protein engineering, and a strong publication record or proven track…