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AI/ML Scientist
$140k – $225k/yr Multiple locations on-site full time senior Apr 13, 2026
Skills
About this role
Manifold Bio is a platform biotechnology company pioneering AI-guided protein design and massively multiplexed in vivo screening to unlock tissue-targeted medicines and organism-scale models of living systems. Using proprietary molecular barcoding technology, we screen hundreds of thousands of protein designs simultaneously in living systems, producing in vivo-validated datasets at a scale no one else can match. The datasets power our computational models, which leads to better drug designs, creating a flywheel that gets stronger with every campaign. Our team of protein engineers, biologists, and computational scientists works across this full stack to pursue programs both internally and with leading pharma companies.
Position
Manifold Bio is seeking an exceptional Machine Learning Scientist to lead research initiatives within our AI team and drive innovation in protein design methodologies. This role will support and enrich the team’s current generative de novo protein design capabilities, as well as break ground on building foundational models on relevant protein therapeutic properties including binding affinity, developability, and in vivo biodistribution and pharmacokinetic (PK) properties. You will be expected to independently conceive, design and execute high-impact research projects that push the boundaries of AI applications in protein design, while contributing to publications and representing Manifold’s scientific contributions to the broader research community.
This is an on-site role and can be based in either Boston, Massachusetts or San Francisco, California. Please only apply if you reside in these cities or are open to relocate.
Responsibilities
Lead independent research projects exploring novel AI/ML approaches for protein design and optimization
Investigate and integrate novel data types to enhance our binder design capabilities and therapeutic development
Develop and validate cutting-edge machine learning methodologies for molecular engineering applications
Mentor and guide junior scientists and engineers in advanced ML techniques and research methodologies
Drive strategic research planning and identify promising new directions for AI-driven drug discovery
Lead cross-functional teams to translate research breakthroughs into therapeutic applications
Provide scientific expertise for business development opportunities and strategic partnerships
Required Qualifications
PhD in Machine Learning, Computational Biology, Bioinformatics, Computer Science, or related field
5+ years of industry experience in machine learning research, preferably in biotechnology or pharmaceutical settings
Expert-level proficiency in PyTorch and/or JAX with extensive experience in novel architecture development
Deep expertise in protein structure analysis, molecular dynamics, computational biology, or structural bioinformatics
Extensive knowledge of modern AI advances in protein analysis, design, and optimization
Advanced understanding of deep learning architectures, particularly transformers for molecular applications, as well as generative modeling approaches (autoregressive, diffusion, flow-matching, etc.)
Proven experience leading research teams and mentoring junior scientists
Strong background in statistical analysis, experimental design, and rigorous scientific methodology
Experience with distributed computing, high-performance computing, and large-scale ML system design
Outstanding written and verbal communication skills with experience presenting to scientific and business audiences
Demonstrated ability to translate research innovations into practical applications
Preferred Qualifications
Previous experience in biotech/pharma industry with focus on AI-driven drug discovery
Knowledge of protein engineering, directed evolution, or structural biology wet lab techniques
Experience with large-scale data engineering, cloud platforms, and production ML systems
Demonstrated track record of published research in top-tier ML, computational biology, or protein design journals
Track record of successful grant funding and research proposal writing
Experience with regulatory considerations for AI applications in therapeutic development
Strong network within the computational biology and protein design research communities
Demonstrated leadership in cross-functional scientific teams
Experience with intellectual property development and patent applications
This Role Might Be Perfect For You If
You are passionate about leveraging state of the art machine learning approaches to solve challenging disease areas
You have rich AI/ML experience and are looking to pivot into biotech
If you're excited to build scalable ML systems that revolutionize protein therapeutic discovery, please reach out to mailto:careers@manifold.bio.
Base Salary Range: $140,000-225,000
This reflects the typical offer range for this role, based on experience, role scope, and internal equity. Final compensation decisions are made using a consistent leveling framework and consider the candidate’s experience, interview performance, and expected impact.
This role is eligible for:
Annual performance-based target bonus
Stock options
Comprehensive medical, dental, and vision coverage
401(k) plan
Flexible paid time off and holidays
Perks including on-site gym, onsite lunch, and commuter support
Our compensation ranges are reviewed annually to ensure alignment with market trends and internal equity.
We value different experiences and ways of thinking and believe the most talented teams are built by bringing together people of diverse cultures, genders, and backgrounds.
Offices: Boston, Massachusetts, United States (Boston Office); San Francisco, California, United States (San Francisco Office);