AI/ML Scientist

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. Location 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 Ideal Candidate 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. Contact If you're excited to build scalable ML systems that revolutionize protein therapeutic discovery, please reach out to View email address on click.appcast.io. Compensation 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. Benefits 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 Diversity Statement 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. #J-18808-Ljbffr