Position

Manifold's AI team is actively training protein foundation models on our proprietary experimental datasets. Our generative antibody design model, mBER, has already demonstrated controllable de novo binder design across multiple million-scale screening campaigns, and the team is now scaling foundation model capabilities to push well beyond current performance. We are looking for an AI/ML Scientist to join this effort. You will work alongside our existing model training team to accelerate the development of foundation models fine-tuned on Manifold's data, bringing additional depth in pre-training methodology, architecture development, and large-scale training. Your work will directly improve mBER's design capabilities and unlock new modeling paradigms for the broader team. You'll own foundation model projects end-to-end, from architecture selection and training infrastructure to evaluation against real experimental outcomes, while contributing to the team's shared research agenda.

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

• Advance the team's ongoing foundation model training efforts—pretraining, fine-tuning, and evaluating folding, docking, language, and generative design models on Manifold's proprietary experimental data
• Bring depth in training methodology, architecture selection, and optimization to complement the existing team's expertise
• Develop and scale training pipelines for distributed, multi-GPU and multi-node training runs
• Integrate foundation model outputs into mBER to improve binder design success rates and enable new design capabilities
• Design and execute ML experiments with clear hypotheses, rigorous evaluation frameworks, and systematic analysis
• Establish best practices for mixed-precision training, gradient checkpointing, and computational efficiency at scale
• Produce clear documentation and analysis supporting architecture and training decisions

Required Qualifications

• Demonstrated experience pretraining and/or fine-tuning protein foundation models (folding, docking, language models, or generative design) with published or otherwise demonstrable results
• Strong familiarity with AlphaFold architecture and training methodology
• 2+ years of hands-on experience with PyTorch and/or JAX for deep learning
• Experience with large-scale model training: distributed training, multi-GPU/multi-node setups, mixed precision, gradient checkpointing
• Solid understanding of deep learning architectures (transformers, attention mechanisms, diffusion/flow matching) and optimization techniques
• Experience working with protein structure data (PDB, mmCIF) and/or protein sequence datasets
• Strong statistical analysis and experimental design skills
• Proficiency in Python scientific computing stack (NumPy, Pandas, scikit-learn)
• Self-directed researcher who can balance guidance with independence
• Excellent written and verbal communication skills for cross-functional collaboration

Preferred Qualifications

• Experience with protein generative design methods (e.g., RFdiffusion, ProteinMPNN, flow matching approaches)
• Experience with protein language models (e.g., ESM family)
• Published research in computational biology, protein design, or structural biology
• Experience training on proprietary or domain-specific biological datasets
• Familiarity with Ray for distributed computing
• Experience with Kubernetes (EKS) and cloud computing platforms (AWS)
• Knowledge of protein engineering, directed evolution, or structural biology wet lab techniques
• Experience working with agentic AI coding tools for fast, parallelized execution of modeling experiments
• Previous biotech/pharma industry experience

This Role Might Be Perfect For You If:

• You have deep experience training protein foundation models and want to apply that expertise to some of the richest proprietary experimental datasets in the field
• You're excited about pushing beyond public model performance by leveraging unique, large-scale in vivo screening data
• You thrive in high-ownership roles where you can drive research direction while collaborating with a tight-knit, world-class team
• You want your models to directly impact real drug discovery programs

If you're excited to train the next generation of protein foundation models on uniquely powerful experimental data, 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 an exceptional Computational Scientist to join our growing Quantitative Biology team. You will work closely with experimental scientists to design and analyze highly multiplexed protein library experiments. You will specifically be working with traditional phage and yeast display readouts, as well as other proprietary display data. You will be expected to own and independently advance projects in areas related to your deep expertise such as protein design, DNA library design, or machine learning/biophysical modeling from MPRA data. You will work closely with our Head of Platform and our other computational scientists to onboard new capabilities that advance the M-Design platform for data-driven engineering of drugs with desired properties.

Responsibilities

• Invent new quantitative protein engineering assays working with experimental scientists
• Build robust data pipelines with rich metrics and statistics for real-time dataset analysis and reporting
• Perform analysis and "hit calling" support, contributing new insights to active projects
• Improve library design workflows to best co-optimize antibody libraries for enhanced performance
• Write and contribute robust code in shared libraries for common protein design tasks
• Collaborate on designing high-throughput experiments and analyze/interpret results from phage display (biopanning, phi-seq, in vivo) and yeast display platforms
• Deliver high-quality data reporting through slides and documentation for cross-functional teams
• Proactively share findings with colleagues through excellent documentation and discussions

Required Qualifications

• PhD and/or 4+ years of equivalent experience in computational biology, bioinformatics, protein engineering, antibody engineering, or similar field working with biological sequences
• Rich experience with Python, agentic coding, data pipeline development
• Familiarity with version control, test-driven development, and Unix computing
• Strong antibody engineering background with first-hand experience in antibody design, optimization, or discovery
• Experience with massively parallel reporter assays (MPRAs) and high-throughput screening data analysis
• Experience designing DNA libraries for binders, DMS, phage display, or equivalent high-throughput experiments
• Experience working with Next Generation Sequencing (NGS) data from library-based experiments
• Strong understanding of statistics fundamentals and data analysis methodologies
• Outstanding written and verbal communication skills for cross-functional collaboration

Preferred Qualifications

• Intuition or exposure to best practices in software/data engineering
• Industry experience in antibody therapeutic development or biotechnology R&D
• Track record of developing computational tools or pipelines adopted by experimental teams
• Experience mentoring junior scientists or leading cross-functional project teams
• Publications or patents in antibody engineering, protein design, or high-throughput screening methods
• Familiarity with cloud computing platforms (AWS, GCP) and containerization technologies

This Role Might Be Perfect For You If

• You thrive in collaborative environments where computational insights directly guide experimental decisions
• You're energized by translating complex datasets into actionable recommendations for drug discovery teams
• You enjoy building robust, production-quality tools that others rely on for critical decisions
• You're passionate about the therapeutic potential of engineered antibodies and want to accelerate their development
• You love working at the intersection of cutting-edge computational methods and innovative experimental platforms

Base Salary Range: $118,000-138,000

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.

If you’re excited to build a platform that combines these technologies to revolutionize how protein therapeutic discovery happens, please reach out to careers@manifold.bio.

Position

We are seeking a highly-motivated In Vivo Pharmacology Senior Research Associate  who thrives in a fast-paced and creative environment to push the capabilities of our multiplexed in vivo drug discovery platform. Together with senior researchers, you will play a critical role in executing in vivo studies to support internal research projects. This is a hands-on role and you should have extensive experience in multiple aspects of in vivo pharmacology including dosing, necropsy, perfusion, tissue collection and  sample processing, among others. The ideal candidate must be able to work effectively both in a collaborative setting and independently. 

Responsibilities

• Conduct in vivo mouse studies, including dosing via IV, IP, SQ, and other routes as needed.
• Perform necropsy, tissue dissection, perfusion, and blood/tissue collection (in-life and terminal
• Perform blood collections via submandibular cheek bleeds and cardiac punctures.
• Prepare and process tissues for downstream analysis.
• Accurately label samples, track collection, and maintain comprehensive records.
• Follow protocols rigorously and contribute to protocol refinement when needed.
• Ability to follow SOPs and work independently in a high-throughput setting.
• Maintain accurate and organized data entry and analysis.
• Collaborate with cross-functional teams in a dynamic research environment.
• Strong attention to detail with excellent data organization and recordkeeping.
• Assist in maintaining inventories.

Required Qualifications

• Bachelors or Masters and 1-2+ years of experience (biotech/pharma industry preferred) in executing in vivo pharmacology experiments in mice
• Demonstrated expertise executing hands-on in vivo studies
• Collaborative, curious, and flexible with strong communication skills, both written and oral
• Self-motivated, highly organized,  able to work independently with minimal supervision, and able to multitask
• Strong attention to detail
• A genuine passion for science and developing medicines

Preferred Qualifications

• Familiarity with histology, microscopy, or tissue sectioning
• Experience in bioanalytical assays for protein therapeutics (PCR, nucleic acid extraction, ELISA, Western Blot, etc)
• Skilled with common data analysis and productivity software such as Microsoft Office, GraphPad Prism, and ImageJ.
• Experience  writing detailed research project plans and methodological SOPs that guide yours and other team members’ laboratory activities
• Experience in mouse health monitoring is highly preferred

Base Salary Range: $70,000-108,000

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

We are seeking an exceptional scientist with expertise in library-based methodologies and substantial wet-lab experience to join our team. In this role, you will lead comprehensive library-based projects from conception to completion, engineering therapeutic proteins with transformative potential. You will develop and execute novel high-throughput screening assays, design and construct DNA libraries using advanced cloning techniques, and analyze complex library screens, including massively parallel in vivo screens powered by our proprietary mCode protein barcoding technology. You will work with a highly interdisciplinary team of creative experimental, computational, and hybrid scientists to advance high-throughput protein engineering and synthetic biology initiatives. As a key member of our growing company, you will contribute to building a culture that embraces scientific boldness and a strong team-focused approach to solving problems.

Required Qualifications

Wet Lab Expertise:

• Masters/PhD or equivalent experience in molecular biology, bioengineering, or a related field.
• Proficiency in standard molecular biology techniques and protocols.
• Hands-on experience with phage-based display approaches.
• Experience designing and constructing diverse DNA libraries for protein engineering applications.
• Proven capability in library-based protein engineering, including experience with high-throughput or multiplexed assay formats.
• Skilled in designing, executing, and analyzing complex experimental workflows from end to end.

Core Competencies:

• Detail-oriented with exceptional organizational and communication skills.
• Curious and flexible, with a strong desire to work collaboratively within a fast-paced and multidisciplinary team environment.
• A love for tinkering with biological parts and solving challenges to develop novel assays.
• Enthusiasm for combining rational design with unbiased approaches to problem-solving.

Preferred Qualifications

• 2+ years of start-up, biotech, or pharma experience in protein engineering or assay development.
• Direct experience with display technologies and selections including phage, yeast, and/or ribosome display.
• Hands-on experience with generating and maintaining overexpression cell lines.
• Hands-on experience with Next Geneneration Sequencing (NGS).
• Experience with handling/processing animal tissues.
• Experience developing or engineering brain shuttle technologies for improved blood-brain barrier transport.
• Familiarity with screening-based methods with an NGS readout, e.g. DMS, MPRA, CRISPR screening, cancer screens, single cell sequencing.
• Experience with data analysis (Python or R).

Base Salary Range: $118,000-138,000

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 an exceptional Senior Director of Biotherapeutics to help guide and mature our discovery, characterization, and production of shuttled therapeutics. This role spans discovery and nonclinical development, including bioengineering strategies to generate best-in-class molecules and oversight of external contract manufacturing organizations (CDMOs) to develop processes and manufacture drug product for clinical trials.

As a member of our leadership team, you will contribute to high-level strategy and help build internal resources to support our ambitious growth plans. This is a unique opportunity to shape the future of a cutting-edge biotechnology company while working with a collaborative, innovative team.

Key Responsibilities:

Team Management & Development

• Manage and mentor internal protein scientists and protein engineers
• Build and focus teams in a capital-efficient manner to support current and future pipeline needs
• Foster strong collaborative interactions between biotherapeutics teams and teams supporting AI/ML protein design and screening, oligonucleotide therapeutic discovery, and pharmacology

Program Execution

• Support the discovery and characterization of shuttled therapeutics via 1-2 matrix project teams, serving as biotherapeutics lead or project lead
• Map out critical path activities through IND-enabling studies and ensure key activities are resourced and executed efficiently
• Engage with consultants, contractors and  CROs/CDMOs to efficiently build expertise and capabilities that accelerate program progression
• Set and implement strategy for developability assessment and early-stage de-risking
• Prepare and present data packages for partnering discussions and investor presentations

Strategic Leadership

• Contribute to high-level strategy and key objectives for discovery and development of shuttled therapeutics
• Establish development candidate nomination criteria for novel biotherapeutics with particular focus on developability metrics 
• Identify and outline opportunities for backup molecule discovery and selection

Qualifications:

Required Experience & Skills

• Extensive experience in biotherapeutics across a range of protein modalities
• Proven track record engineering antibodies for clinical development
• Deep knowledge of state-of-the-art protein engineering approaches
• Experience with protein expression systems, purification methods, and characterization including developability assays
• Prior experience liaising with CDMOs

Preferred Qualifications

• Expertise with novel modalities and complex formats, including ADCs, tissue-targeted therapeutics, and bispecific antibodies
• Understanding of high-throughput screening and bioanalytical technologies
• Experience with generative AI models for protein and/or oligonucleotide design

Base Salary Range: $240,000-340,000

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 scientist to build and own a high-throughput, automated cell-free display platform for screening computationally designed protein binder libraries against hundreds of therapeutic receptor targets. This platform will be a cornerstone of Manifold's closed-loop AI-driven molecule discovery engine, generating the large-scale, high-quality binding data needed to train and improve our design models. The ideal candidate is a hands-on scientist with deep expertise in cell-free display technologies and a drive to build automated systems that can operate at scale. You will work at the intersection of protein engineering, laboratory automation, and ML-guided drug discovery, collaborating closely with our binder discovery, ML, and automation teams.

Responsibilities

• Design, develop, and validate a cell-free display platform (cDNA display or similar) compatible with diverse binder formats 
• Work with automation team to scale and automate the platform to enable routine, high-throughput screening against large panels of therapeutic targets
• Collaborate with ML and computational teams to ensure screening outputs feed effectively into model training pipelines
• Work with the protein engineering team to support discovery campaigns and affinity maturation as platform capacity allows 
• Stay current on advances in cell-free display, laboratory automation, and computational protein design

Required Qualifications

• PhD or equivalent experience in protein biochemistry, molecular biology, biological engineering, or a related field
• Hands-on experience with cell-free selection systems (cDNA display, mRNA display, ribosome display, or similar)
• Strong molecular biology fundamentals and demonstrated ability to develop and troubleshoot complex, multi-step workflows
• Experience with or strong interest in laboratory automation

Preferred Qualifications

• Track record of successfully automating complex laboratory workflows
• Background in therapeutic antibody discovery or protein engineering 
• Experience with computational protein design
• Familiarity with how high-throughput screening data feeds into ML and computational pipelines
• Experience with complex or non-traditional binder formats and biochemical intuition to adapt selection workflows accordingly

Why you might be a good fit

• Building systems that generate data at a scale previously impossible excites you
• You thrive in fast-moving environments where you own a problem end-to-end
• You are energized by working at the intersection of wet lab science, automation, and AI-driven biotherapeutic discovery
• You are a collaborative scientist who communicates well across teams with different technical backgrounds

Base Salary Range: $118,000-138,000

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 an experienced drug development leader to guide strategy and execution of our shuttled oligonucleotide therapeutics programs. You will define and execute the strategic vision for our oligonucleotide therapeutic capabilities, leveraging our proprietary shuttle screening technology to discover and develop the next generation of  tissue-targeted oligonucleotide therapeutics. This role combines technical leadership of scientific staff focused on designing, screening, and evaluating tissue-targeted oligonucleotides, with strategic leadership of cross-functional drug discovery teams advancing lead molecules toward clinical testing.

Responsibilities

• Build and lead a fit-for-purpose oligonucleotide therapeutic discovery team that includes both internal and outsourced expertise and capabilities, as needed.
• Lead 1-2 cross-functional drug discovery project teams, collaborating closely with protein engineers, in vitro biologists, bioconjugation scientists, and in vivo biologists to discover and progress shuttled oligo-based therapeutics.
• Work with company leadership and cross-functional experts to prioritize high-value therapeutic targets for tissue-targeted oligo therapeutics. 
• Define best-in-class target product profiles for tissue-targeted therapeutic oligonucleotides. Define workplans and track progress to deliver on those target product profiles.
• Closely track advances in the field and provide strategic direction for continued development and expansion of Manifold’s shuttled oligo discovery efforts.
• Clearly communicate scientific progress and challenges to team members, leadership, and internal/external  collaborators
• Establish and optimize innovative,  efficient screening and production systems that leverage Manifold’s multiplexed in vivo screening capabilities. 
• Serve as oligonucleotide therapeutic subject matter expert  in discussions with potential partners, collaborators, and investors

Required Qualifications

• PhD in a relevant field (chemistry, biochemistry, nucleic acid chemistry/biology, biophysics, molecular biology, pharmacology or related discipline)
• Minimum of 10 years post-PhD experience, including experience in industry drug-discovery programs
• Diverse experience with multiple oligonucleotide modalities (ASOs, siRNAs, aptamers, mRNA), different backbone chemistries/modifications
• Knowledge of proven and emerging technologies for delivering oligo medicines to cellular targets (LNPs, passive or active targeting moieties, etc.)
• Experience progressing oligonucleotide therapies from early discovery through IND-enabling preclinical activities / early clinical development
• Demonstrated leadership of effective specialized and cross-functional scientific teams
• Demonstrated ability to mentor junior scientists
• Excellent written and verbal communication skills

Preferred Qualifications

• Experience designing and interpreting in vitro and in vivo systems assessing oligonucleotide efficacy and safety
• Strong background in the engineering of optimized oligonucleotide conjugates, including linker discovery and bioconjugation optimization 
• Experience building and/or optimizing platforms for oligo design, synthesis, and screening
• Understanding of DMPK, toxicology, developability, and CMC considerations specific to oligos
• Track record of successful partnerships and external collaborations

This Role Might Be Perfect For You If:You are energized by the opportunity to shape the future of a therapeutic modality, working at the intersection of cutting-edge shuttle technology and oligonucleotide medicine. You are a strategic scientific leader who thrives on building complex technical platforms and programs from the ground up. You combine deep oligonucleotide chemistry expertise with the vision and drive to establish new capabilities and lead cross-functional teams toward ambitious goals. You excel at balancing scientific rigor with the speed and agility needed in a dynamic biotech environment, making data-driven decisions that advance programs while managing multiple priorities and stakeholders.

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

Base Salary Range: $195,000-239,000

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 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.

The Opportunity

We are seeking an exceptional Head of Biology to lead the scientific strategy and execution that will realize the full potential of the Manifold platform. You will own the creation of a differentiated pipeline of tissue-targeted therapeutics that are delivered directly to target tissue via novel receptor portals that have been discovered through our platform combining AI-design with in vivo data at scale. You will directly lead our discovery biology and pharmacology teams, while also serving as the accountable leader for 1-2 drug-discovery matrix project teams from product concept through IND.

As a member of our R&D leadership team, you will set pipeline and portal prioritization strategy and represent Manifold's science with potential business partners, investors, and KOLs. Our initial focus is CNS: brain-shuttled mAbs and oligonucleotides leveraging novel BBB portals, with expansion opportunities into other tissue targets and modalities.

Key Responsibilities

• Build and oversee a research organization of highly effective discovery biology and pharmacology scientists, directly managing 2-4 team leads.
• Efficiently prioritize workflows to discover tissue-targeting shuttles and shuttled therapeutics, translating platform capabilities into a best-in-class portfolio of tissue-targeted medicines.
• Provide effective leadership for 1-2 cross-functional drug discovery project teams, integrating biology, therapeutic discovery/engineering, pharmacology, and preclinical development expertise.
• Craft and deliver effective scientific presentations for leadership, board members, potential partners, and investors. 
• Partner with functional leads to recommend staffing, resourcing, and critical-path activities necessary to deliver IND-ready assets and lead molecules that achieve partner research milestones.
• Provide technical mentorship on experimental design, data interpretation, and scientific communication. Ensure experimental plans are rigorous, efficient, and deliver data that support clear actions and decisions.
• Collect, review and update datasets from both platform and project teams. Lead internal discussions to deliver data-driven recommendations of priorities and next steps. 
• Cultivate a collaborative, execution-oriented culture that moves quickly without compromising quality or rigor.
• Build strong collaborative relationships with scientists in AI/ML, platform discovery, and  biotherapeutic engineering, leveraging diverse perspectives and sources of expertise to make the right scientific decisions.
• Serve as the scientific liaison with external partner R&D leadership to scope, negotiate, and execute research and development partnerships. Serve on or advise partner Joint Research Committees. 

Qualifications

• Education and Experience: PhD in molecular biology, biochemistry, pharmacology, neuroscience, pathology, or a closely related discipline; 10+ years of biopharma R&D experience for VP level, or 7+ years for Senior Director level
• Drug-hunter track record: Demonstrated advancement of multiple discovery programs from concept through Development Candidate, with at least one program advanced into Phase 1 strongly preferred. Ability to understand and use regulatory, clinical and CMC considerations to inform TPP, early discovery priorities, and key go/no-go experiments.  Hands on experience with multiple modalities, preferred experience with antibodies, antibody: drug conjugates, fusion proteins, or oligonucleotides.
• Therapeutic area expertise: Deep domain knowledge of underlying biology associated with a major therapeutic area. CNS preferred, with cardiometabolic, muscular/neuromuscular, pain, fibrosis, pulmonary and kidney disease also of interest. Familiarity with BBB biology, receptor-mediated transcytosis, PK/PD modeling, and/or tissue-targeting modalities is a strong plus.
• Team leadership: Track record of building, managing, and developing multidisciplinary discovery organizations of 5+ scientists; proven ability to recruit and retain senior scientific talent. In addition, demonstrated experience leading or serving as core member of matrixed drug-discovery project teams in biotech or pharma
• Bioanalytical assay design and interpretation: experience bringing both innovation and rigor to the design of high-quality, high-throughput assays. Ability to transfer research-grade assays to automation platforms and qualified CROs.

• Developability & IND awareness: Working knowledge of CMC, developability, and IND-enabling requirements sufficient to make program-level decisions and resource CMC/CDMO work appropriately.
• Communication: Outstanding written and verbal communication; ability to adjust framing to audiences ranging from junior scientists to experienced biopharma leaders and generalist investors.
• Agile leadership: comfortable in a fast-moving, agile organization where leaders must directly drive execution. 
• Humble, team-first, and collaborative; brings joy and energy to work and inspires those around them; deep passion for the science and the patients it serves

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.

Base Salary Range: $240,000-340,000

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.