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 a Product Manager to serve as the internal product owner for our AI projects, leading the roadmap across key domains including protein design, foundation models, reasoning models, agents, and infrastructure. This role covers both  internal product management and liaising with AI / tech partners., Internal responsibilities include interfacing with the AI team and R&D project managers to translate ambitious AI x biology ideas into shipped internal products and platform capabilities. External responsibilities include developing and nurturing relationships with external AI teams and partners, with an opportunity to flex into business development and strategic transactions. This role works closely with our co-founders, AI/ML leadership, and BD team to turn cutting-edge capabilities into durable platform assets.

Responsibilities

• Define the product vision, roadmap, and success metrics for Manifold’s AI platform capabilities, including protein design, foundation models, and agents
• Translate internal R&D and AI x biology ideas into concrete requirements and run the operating cadences that drive decisions and accountability
• Own Manifold's strategy for engaging the AI ecosystem; decide which partners to prioritize, what to build with each, and how to sequence engagements
• Coordinate cross-functional execution across AI/ML, protein engineering, biology, and platform teams for partnerships and platform development
• Source, qualify, and close new AI partnership opportunities, leading exploratory conversations through to signed scope
• Own the quality of all external deliverables including reports, decks, and demos, and produce executive-ready memos to align internal stakeholders

Required Qualifications

• 2+ years of product management, technical program management, alliance management, or BD experience, with at least part of that in AI/ML or computational product environments
• Bachelor's degree in a technical field (CS, engineering, biology, or related); advanced degree a plus
• Demonstrated ability to own complex, ambiguous strategic relationships and drive them to concrete value generating outcomes
• Strong working knowledge of modern AI/ML concepts (foundation models, training and evaluation, agentic systems, scaling laws) and how they apply to scientific and industrial problems specific to drug discovery 
• Familiarity with biology, protein engineering, drug discovery, or another applied scientific domain
• Exceptional written communication; ability to produce executive-ready memos, decks, and external deliverables independently
• Track record of running cross-functional execution in matrixed organizations and shipping on aggressive timelines
• Comfort operating in high-ambiguity, fast-evolving partnerships where the product itself is being defined as you go
• Demonstrated handle of agentic coding skills; e.g. ability to rapidly run analyses / generate figures

Preferred Qualifications

• Experience building or shipping products at a frontier AI lab, AI infrastructure company, or AI-first startup
• Experience structuring partnership terms in collaboration with BD and legal (data rights, IP, joint roadmaps)
• Public writing, talks, or other evidence of unusually strong communication ability
• Experience scaling a partnership function or building partnership operating processes from scratch

If you’re excited to use unique protein technologies to shape an innovative drug development strategy, build meaningful industry partnerships, and contribute directly to our mission of advancing breakthrough treatments, please apply!

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 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.

Position

Manifold Bio is seeking a talented Machine Learning Research Engineer to join our growing AI team. You will work closely with our research scientists to implement, scale, and optimize machine learning systems that power our de novo antibody design platform and advance our protein design capabilities. Your efforts will contribute to building production-ready ML infrastructure that enables breakthrough discoveries in protein therapeutics. You will be expected to take ownership of engineering challenges in our ML pipeline, from data processing and model training to deployment and monitoring, while collaborating closely with our research team to translate cutting-edge ideas into robust, scalable systems.

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

• Implement and optimize machine learning models for protein design
• Build and maintain scalable data processing pipelines for large-scale protein and molecular datasets
• Develop and deploy ML infrastructure for distributed training and inference across GPU clusters
• Collaborate with research scientists to translate experimental ML approaches into production-ready code
• Design and execute ML experiments with clear hypotheses and rigorous analysis
• Optimize model performance and computational efficiency for large-scale protein design tasks
• Build tools and utilities to support rapid prototyping and experimentation by the research team

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Machine Learning, Computational Biology, or related field
• 2+ years of hands-on experience with PyTorch and/or JAX for deep learning applications
• Strong proficiency in Python scientific computing stack (NumPy, Pandas, scikit-learn)
• Experience with distributed computing and GPU optimization techniques
• Familiarity with protein structure analysis, computational biology, or analogous problems in natural sciences
• Understanding of modern deep learning architectures and optimization techniques
• Experience implementing research papers or translating ML approaches to production systems
• Proficiency with version control (Git), testing frameworks, and software engineering best practices
• Strong problem-solving skills and ability to work independently on technical challenges
• Excellent written and verbal communication skills for cross-functional collaboration

Preferred Qualifications

• Experience training LLMs or diffusion generative models
• Knowledge of cloud computing platforms (AWS, GCP) and containerization (Docker, Kubernetes)
• Background in computational biology, bioinformatics, or structural biology
• Experience with large-scale data engineering and ETL pipelines
• Familiarity with MLOps practices and model deployment frameworks

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 enjoy translating research ideas into high impact, productionized, scalable code
• 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 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.