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

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.

About the Position

As the Director of Data Science at Formation Bio, you will be at the forefront of revolutionizing drug development through AI and advanced analytics. In this role, you'll lead crucial initiatives that directly impact our drug development portfolio, from developing sophisticated models for patient selection to creating AI-powered solutions for clinical trial optimization. You'll work at the intersection of computational biology, machine learning, and drug development, collaborating with cross-functional teams to translate complex biological data into actionable insights. This position offers a unique opportunity to shape the future of pharmaceutical development by leveraging cutting-edge AI technologies while making a meaningful impact on patient lives. 

Responsibilities

• Lead and execute complex data science projects that directly advance our drug development portfolio 
• Develop and implement sophisticated models for therapeutic hypothesis evaluation, including patient stratification and biomarker identification
• Design and create AI models for modernizing clinical trial evaluations, including surrogate endpoints 
• Aid in the development and training of AI agents to automate and optimize biomedical workflows 
• Collaborate cross-functionally with clinical, technical, and research teams 
• Present complex analytical findings to senior stakeholders, including executive leadership 

About You

Required Qualifications 

• PhD in computational sciences or life sciences 
• 7+ years of post-academic experience in life sciences (biotech, pharma, consulting) 
• Strong programming skills, particularly in Python 
• Extensive experience in multi-modal bioinformatics analysis 

Preferred Qualifications 

• Proven expertise in cloud computing environments, including proficiency with tabular and/or graph databases 
• Strong background in machine learning and deep learning, particularly in biological applications 
• Experience with large language models (LLM)
• Demonstrated ability to collaborate effectively with engineering teams on production systems
• Strong communication skills with proven ability to present complex technical findings to senior stakeholders 

Total Compensation Range: $235,000 - $307,000

About the Position

As a Senior Data Scientist at Formation Bio, you will be at the forefront of revolutionizing drug development through AI and advanced analytics. In this role, you'll lead crucial initiatives that directly impact our drug development portfolio, from developing sophisticated models for patient selection to creating AI-powered solutions for clinical trial optimization. You'll work at the intersection of computational biology, machine learning, and drug development, collaborating with cross-functional teams to translate complex biological data into actionable insights. This position offers a unique opportunity to shape the future of pharmaceutical development by leveraging cutting-edge AI technologies while making a meaningful impact on patient lives. 

Responsibilities

• Lead and execute complex data science projects that directly advance our drug development portfolio 
• Develop and implement sophisticated models for therapeutic hypothesis evaluation, including patient stratification and biomarker identification
• Design and create AI models for modernizing clinical trial evaluations, including surrogate endpoints 
• Aid in the development and training of AI agents to automate and optimize biomedical workflows 
• Collaborate cross-functionally with clinical, technical, and research teams 
• Present complex analytical findings to senior stakeholders, including executive leadership 

About You

Required Qualifications 

• PhD in computational sciences or life sciences 
• 3+ years of post-academic experience in life sciences (biotech, pharma, consulting) 
• Strong programming skills, particularly in Python 
• Extensive experience in multi-modal bioinformatics analysis 

Preferred Qualifications 

• Proven expertise in cloud computing environments, including proficiency with tabular and/or graph databases 
• Strong background in machine learning and deep learning, particularly in biological applications 
• Experience with large language models (LLM)
• Demonstrated ability to collaborate effectively with engineering teams on production systems
• Strong communication skills with proven ability to present complex technical findings to senior stakeholders 

Total Compensation Range: $170,000 - $215,000

About the Position

As a Principal Data Scientist at Formation Bio, you will be at the forefront of revolutionizing drug development through AI and advanced analytics. In this role, you'll lead crucial initiatives that directly impact our drug development portfolio, from developing sophisticated models for patient selection to creating AI-powered solutions for clinical trial optimization. You'll work at the intersection of computational biology, machine learning, and drug development, collaborating with cross-functional teams to translate complex biological data into actionable insights. This position offers a unique opportunity to shape the future of pharmaceutical development by leveraging cutting-edge AI technologies while making a meaningful impact on patient lives. 

Responsibilities

• Lead and execute complex data science projects that directly advance our drug development portfolio 
• Develop and implement sophisticated models for therapeutic hypothesis evaluation, including patient stratification and biomarker identification
• Design and create AI models for modernizing clinical trial evaluations, including surrogate endpoints 
• Aid in the development and training of AI agents to automate and optimize biomedical workflows 
• Collaborate cross-functionally with clinical, technical, and research teams 
• Present complex analytical findings to senior stakeholders, including executive leadership 

About You

Required Qualifications 

• PhD in computational sciences or life sciences 
• 5+ years of post-academic experience in life sciences (biotech, pharma, consulting) 
• Strong programming skills, particularly in Python 
• Extensive experience in multi-modal bioinformatics analysis 

Preferred Qualifications 

• Proven expertise in cloud computing environments, including proficiency with tabular and/or graph databases 
• Strong background in machine learning and deep learning, particularly in biological applications 
• Experience with large language models (LLM)
• Demonstrated ability to collaborate effectively with engineering teams on production systems
• Strong communication skills with proven ability to present complex technical findings to senior stakeholders 

Total Compensation Range: $204,500 - $267,000

About Rhino Federated Computing

Rhino Federated Computing Rhino solves one of the biggest challenges in AI: seamlessly connecting siloed data, apps, and models through federated computing. Our platform enables our customers to share business insight and processing without compromising intellectual property, data privacy, or data security. Our Rhino Federated Computing Platform offers flexible architecture across multi-cloud and on-prem hardware, end-to-end data management controls and workflows, and privacy enhancing technologies. Rhino is trusted by over 60 leading consortia and enterprises worldwide, including 14 of 20 of Newsweek’s ‘Best Smart Hospitals’ and top 20 global biopharma companies.

The company is headquartered in Boston, with an R&D center in Tel Aviv.

About the Role

As the Team Lead for the Forward Deployed AI Engineering Team, you will serve as a hands-on Player/Coach, leading a customer-facing AI engineering and scientist group responsible for deploying and scaling Rhino’s Federated Computing Platform (FCP) in complex, real-world environments. You will maintain a direct, hands-on contribution by working with customers’ technical and research teams to design, implement, and optimize federated AI models and systems. Critically, you will also coach, mentor, and manage a team of applied AI engineers, guiding them through federated model training, inference, deployment, and monitoring, while helping customers unlock the full potential of federated data collaboration. Your leadership will shape how federated AI is operationalized at scale. 

Key Responsibilities

Technical Leadership & Delivery

• Lead the design and delivery of federated AI solutions across imaging, text, and structured data domains.
• Design and implement federated training and inference pipelines, integrating data preprocessing, model orchestration, and AIOps tooling.
• Own project execution from scoping to deployment — ensuring clarity, speed, and technical excellence.

Customer Engagement & Enablement

• Partner directly with customers to understand workflows, map data ecosystems, and design scalable AI solutions.
• Serve as a trusted technical advisor on privacy-preserving ML, model optimization, and deployment best practices.
  Build long-term relationships that drive adoption and measurable outcomes for customer programs.

Team Leadership 

• Manage multiple concurrent engagements, balancing strategic leadership with hands-on problem-solving.
• Provide mentorship to Forward Deployed Engineers and Scientists, fostering a high-performance, learning-driven culture.

Product Feedback & Innovation

• Identify reusable solution patterns and contribute to the standardization of federated AI workflows.
• Surface customer insights and field feedback that shape Rhino’s roadmap.
• Collaborate with product and research teams to prototype and validate new federated learning research and frameworks.

Required Skills

• Experience: 5+ years in applied AI, machine learning engineering, or MLOps roles; experience deploying models in production environments.
• Technical Expertise: Deep hands-on experience with deep learning frameworks (PyTorch, TensorFlow, JAX) and AI/MLOps ecosystems.
• Generative AI Tools: Familiarity with LLM frameworks (GPT, Gemini, Claude, LangChain, agentic frameworks, etc.).
• Programming & Systems: Strong proficiency in Python, REST APIs, and data systems (SQL/NoSQL); comfort with cloud computing and GPU-based systems.
• Delivery Focus: Proven ability to own technical outcomes end-to-end, from scoping and prototyping to full-scale delivery.
• Collaboration: Excellent communication skills and the ability to operate across customer, product, and engineering teams.
• Mindset: Action-oriented, adaptable, and able to prioritize effectively in fast-changing environments.

Preferred Skills

• Industry experience in healthcare, biopharma, financial services, and public sector.
• Ph.D. or M.S. in a quantitative field (Computer Science, Engineering, Biomedical Informatics, Bioinformatics, Chemistry, or related).
• Prior experience deploying federated learning, privacy-preserving AI, or secure distributed computing systems.

Location 

Boston preferred, but open to other locations for highly qualified candidates.

Visa Sponsorship

We will sponsor visas for USA PhD candidates in the relevant areas - Mathematics, Artificial Intelligence, Federated Learning, Computational Chemistry/Biology/Biomedical candidates. An B.S./M.S. with extensive, directly relevant industry experience will also be considered.

September 24, 2025

Position:   
Senior Computational Biologist/ ML Scientist 

Company Overview:   
At Kernal Bio, we engineer human cells inside the body using selective mRNA-LNP technology to treat cancer and autoimmune diseases. Our AI-designed mRNAs, delivered via antibody-decorated lipid nanoparticles (LNPs), ensure precise targeting and minimize off-target effects. Our KR-402 program focuses on hematological malignancies and autoimmune disorders, achieving >90% in vivo delivery efficiency with T-cell-targeted LNPs. The KR-335 program, targeting solid tumors resistant to standard immunotherapies, shows a 100x therapeutic index with strong efficacy and tolerability in preclinical models, including mice and non-human primates.

With roots at MIT, Harvard, Merck, and BMS, our management team has spearheaded the development of three FDA-approved therapies and holds over 120 patents. Based in Cambridge, MA, and backed by Hummingbird Ventures, Amgen Ventures, NVIDIA, and NASA, Kernal Bio is revolutionizing mRNA therapeutics by leveraging AI to deliver precision treatments within the body. 

Job Summary 

Senior Computational Biologist/ ML Scientist 
We are seeking a Senior Computational Biologist to join our dynamic R&D team and spearhead our drug discovery efforts. This is a chance to move beyond routine data analysis and creatively apply advanced computational methods to solve complex biological challenges. You will be a key driver in designing next generation mRNA therapeutics, directly impacting our pipeline and scientific strategy.

The Role
As a core member of our research group, you will leverage your expertise to extract meaningful insights from diverse datasets. Your primary focus will be on applying sophisticated data science and machine learning techniques to biological questions. You’ll collaborate closely with diverse cross-functional teams, including our wet lab scientists, synthetic biology, and formulation teams, acting as a bridge between data and discovery.

Key responsibilities include:

Data Analysis & Modeling: Design and execute rigorous statistical and computational analyses by integrating and analyzing diverse omics datasets, including genomics, transcriptomics, proteomics, and single-cell sequencing data. You will also be responsible for developing, training, and deploying novel AI/machine learning models to predict biological outcomes and accelerate drug discovery.

High-Performance Computing: Efficiently manage and scale computational workloads by leveraging cloud computing platforms and utilizing NVIDIA GPU-accelerated computing for data processing and model training.

Scientific Communication: Prepare scientific manuscripts, contribute to intellectual property filings, and present your findings at leading scientific conferences and internal meetings.

Documentation & Workflow: Meticulously document all computational workflows, experimental results, and analyses in an Electronic Lab Notebook (ELN) such as Benchling and maintain rigorous version control and facilitate collaborative code development using platforms like GitHub.

Mentorship: Guide and mentor junior team members, sharing your knowledge of best practices in computational analysis and scientific inquiry.

Who We’re Looking For
We are looking for a creative and detail-oriented scientist with a proven track record. You should have a Ph.D. in Computational Biology, Bioinformatics, or a related field, along with a minimum of 3 years of experience in the biopharmaceutical industry.

You are a master of your craft with:

Deep Expertise: A strong background in the analysis of high-throughput biological data, including genomics, transcriptomics, proteomics, and single-cell sequencing.

Modern Skill Set: Experience applying machine learning and AI, with a solid theoretical grasp of algorithms like gradient descent, Bayesian optimization, and other heuristic search methods. Proficiency with large language models (LLMs) is a significant plus.

Accelerated Computing: Hands-on experience with NVIDIA GPU-accelerated computing is highly valued. Familiarity with CUDA, cuDNN, or NVIDIA Clara for bioinformatics applications will set you apart.

Programming Prowess: Exceptional fluency in Python and experience with workflow management systems, with a strong emphasis on version control using Git/GitHub.

Cloud Computing: Hands-on experience with at least one major cloud platform (AWS, Azure, or Google Cloud).

Intellectual Curiosity: A creative, out-of-the-box thinker who is eager to learn new methods and tackle complex problems head-on.

Collaborative Spirit: Excellent communication and time-management skills, with the ability to manage multiple projects and work effectively within cross-functional teams.

Benefits:

• Competitive 401(k)   
• Highly competitive healthcare coverage (PPO/HMO)
• Free parking, a monthly subway pass, or a subsidized commuter rail pass  
• Free Bluebike Membership
• Gym Membership Support   
• Flexible Spending Account 
• Paid parental leave, family caregiver leave, and medical leave  
• Paid life insurance coverage 
• On-site cafeteria  
• Competitive vacation and sick days per year 

Kernal provides a diverse work environment and is committed to equal employment opportunities for all its employees and qualified applicants. We do not discriminate in employment practices for the race, color, national origin, age, gender, sexual orientation, marital or veteran status, religion, disability, or any other legally protected status. Kernal Bio will make reasonable accommodations for qualified individuals with known disabilities in accordance with applicable law.

This role strongly prefers candidates located in the Boston area with the ability to regularly commute to our Seaport headquarters.

Due to the nature of this role, candidates should expect to support U.S. Government customers. Candidates must have the ability to obtain and maintain a U.S. security clearance per business requirements. In connection therewith, candidates must be willing to undergo a background investigation and meet eligibility requirements. Clearance sponsorship will be available.

Candidates who currently hold an active or recently inactive U.S. Government security clearance are encouraged to apply.

Ginkgo Biosecurity is building next-generation biosecurity infrastructure to help governments and partners detect, attribute, and deter biological threats. Our mission extends across public health, national security, and global defense, ensuring nations can rapidly identify dangerous pathogens, understand where threats originate, and respond with confidence.

We are seeking a Senior Full-Stack Software Engineer to join the Biosecurity engineering team. This role is ideal for someone who thrives in cross-disciplinary environments and is excited to build production software that directly supports biosecurity, epidemiology, and biological data workflows. We are looking for an engineer who is not only a technical expert but also a forward-thinker who embraces AI-augmented development and maintains a 'deploy-with-confidence' culture through rigorous CI/CD and automated testing

You will work across the stack—from backend services and data pipelines to user-facing web applications—building reliable, scalable systems that turn complex biological data into actionable insights.

Responsibilities

• Develop high-performance full-stack applications that translate complex biological data and operational needs into intuitive software using Python and modern JavaScript frameworks
• Champion an AI-first mindset, leveraging generative AI tools and LLM-based assistants to accelerate feature development, optimize code quality, and automate routine engineering tasks
• Collaborate with cross-functional domain experts to architect and operate on biological datasets (genomic, diagnostic, or epidemiological), ensuring that surveillance workflows maintain high standards for data integrity, provenance, and security.
• Influence the technical roadmap and long-term evolution of the Biosecurity platform, identifying and mitigating technical debt and architectural bottlenecks before they impact delivery.
• Design and implement robust CI/CD pipelines where automated unit, integration, and security testing are treated as mandatory gates for every code deployment.
• Drive engineering excellence by leading technical design reviews and providing critical feedback on software modularity, while upholding rigorous standards for documentation, observability, and long-term maintainability
• Support production systems by monitoring performance, troubleshooting issues, and continuously improving reliability, including on-call support and triage in off hours

Minimum Requirements

• 6-8+ years of professional software engineering experience, with significant full-stack development work, including ownership of complex systems and cross-team technical initiatives.
• Strong proficiency in Python for backend development (our primary programming language).
• Experience building and consuming APIs (REST and/or GraphQL).
• Experience developing modern web frontends using JavaScript/TypeScript and frameworks such as React.
• Demonstrated ability to integrate AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) into daily workflows to increase productivity and code reliability
• Proven experience collaborating  domain experts (scientific, operations, product, etc) to translate complex biological data (genomic, diagnostic, or epidemiological) into robust software solutions and actionable insights
• Solid grounding in software engineering fundamentals: data structures, system design, version control, and modern CI/CD patterns for automated testing and deployment

Preferred Capabilities and Experience

• Prior experience in bioinformatics, computational biology, public health, or a related domain.
• Familiarity with cloud infrastructure (e.g., AWS) and containerized environments (Docker, Kubernetes).
• Experience with data pipelines, workflow orchestration, or analytics platforms.
• Exposure to regulated or sensitive-data environments (e.g., HIPAA, public health data).
• Demonstrate high levels of ownership and independent execution
• Comfort working in fast-moving, ambiguous problem spaces where requirements evolve
• Flexibility and willingness to work on the highest priority needs of the business

As an AI Research Scientist III at 1910 you will be expected to roll up your sleeves as an Individual Contributor (IC) by keeping up with relevant scientific literature, prototyping promising methods, and contributing to our active drug design campaigns by applying 1910’s productionized AI/ML models. 

Role Description 

• Propose and prototype AI and Machine Learning solutions that address use cases in 1910’s design pipeline  

• Independently apply productized AI and Machine Learning models to advance 1910’s active drug design campaigns  

• Independently write and publish peer reviewed scientific articles  and mentor junior AI Researchers with their work  

• Periodically presenting recent AI research at internal journal clubs  

• Work cross-functionally with scientific colleagues, being a subject matter expert in how AI and Machine Learning can be used to answer cheminformatics and bioinformatics questions  

• Keep up-to-date on cutting-edge research in the AI for drug discovery space  

• Manage junior AI Research Scientists including having weekly 1:1s, and regular performance reviews  

Qualifications 

• PhD in a relevant discipline (Computer Science, Biology, Chemistry, etc.) 

• 3+ years of relevant industry experience (AI, Drug Discovery, etc.) 

• A strong understanding of statistics and classical machine learning methods (SVM, RF, etc.)  

• Industry experience training and deploying cutting edge deep learning methods (Transformers, Graph Neural Networks, etc.)  

• Wet lab validation of at least 2 AI-driven drug discovery initiatives 

• Demonstrated experience writing clean, maintainable, production-quality Python code, with examples available in code repositories 

• Familiarity with MLOps and DevOps best practices  

• Exposure to distributed computing (Microsoft Azure, HPC Cluster, etc.)  

• Strong track record of publications of individual research in top-tier AI journals and conferences   

• Ability to demonstrate business value related to developed AI and Machine Learning solutions in biology and medicinal chemistry related to your modeling efforts 

• Ability to work effectively in a fast-paced startup environment with evolving projects and shifting priorities driven by business needs 

• Excellent written and verbal communication skills, including the ability to create clear documentation for roadmaps, proposals, and related materials 

Nice to Haves 

• Past experience managing junior AI Research Scientists  

#LI-Onsite

As an AI Research Scientist II at 1910 you will be expected to roll up your sleeves as an Individual Contributor (IC) by keeping up with relevant scientific literature, prototyping promising methods, and contributing to our active drug design campaigns by applying 1910’s productionized AI/ML models. 

Role Description 

• Propose and prototype AI and Machine Learning solutions that address use cases in 1910’s design pipeline  

• Apply productized AI and Machine Learning models to advance 1910’s active drug design campaigns with minimal support from senior members of the AI Research Team 

• Write and publish peer reviewed scientific articles with minimal support from senior members of the AI Research Team 

• Periodically presenting recent AI research at internal journal clubs  

• Work cross-functionally with scientific colleagues, being a subject matter expert in how AI and Machine Learning can be used to answer cheminformatics and bioinformatics questions  

• Keep up-to-date on cutting-edge research in the AI for drug discovery space  

Qualifications 

• PhD in a relevant discipline (Computer Science, Biology, Chemistry, etc.) 

• 2 years of relevant industry experience (AI, Drug Discovery, etc.) 

• A strong understanding of statistics and classical machine learning methods (SVM, RF, etc.)  

• Industry experience training and deploying cutting edge deep learning methods (Transformers, Graph Neural Networks, etc.)  

• Wet lab validation of at least 1 AI-driven drug discovery initiatives 

• Demonstrated experience writing clean, maintainable, production-quality Python code, with examples available in code repositories 

• Familiarity with MLOps and DevOps best practices  

• Exposure to distributed computing (Microsoft Azure, HPC Cluster, etc.)  

• Strong track record of publications of individual research in top-tier AI journals and conferences   

• Ability to demonstrate business value related to developed AI and Machine Learning solutions in biology and medicinal chemistry related to your modeling efforts 

• Ability to work effectively in a fast-paced startup environment with evolving projects and shifting priorities driven by business needs 

• Excellent written and verbal communication skills, including the ability to create clear documentation for roadmaps, proposals, and related materials 

#LI-Onsite

About Watershed

Our vision is to become the leading biocomputing platform. The future of biology is in big data analysis, and we are on a mission to accelerate digital drug discovery with the Watershed platform. Watershed enables scientists to conduct all essential analysis — from lab data to plot — with a single software platform. 

We have attracted some of the best bioinformatics, engineering, and commercial talent, and we are growing! Join a team that’s intellectually curious with a bias for action, headquartered in Cambridge, Massachusetts, composed of people who have come together to enable outcomes while empowering the research of all those committed to changing lives — all while bringing transformational change to a $40 billion industry.

Responsibilities

• Integrate software libraries and cluster computing frameworks into high performance applications
• Develop solutions for benchmarking, metric collection, and monitoring of resources
• Collaborate with software engineers to optimizing software and maximize computational throughput

Qualifications

• Experience in all of the following areas: parallel computing, distributed computing, computer architecture, and software optimization
• Programming experience in Python, C/C++, and Bash
• Experience working with Unix/Linux, containerization, and cloud environments
• Familiarity with networking, security, and the Linux operating system
• Ability to analyze very complex problems and come up with novel solutions

Watershed is an equal-opportunity employer and believes diversity of all types is integral to company success. We do not discriminate on the basis of religion, sexual orientation, gender identity, race, ethnicity, national origin, marital status, veteran status, or disability status.

About Watershed

Our vision is to become the leading biocomputing platform. The future of biology is in big data analysis, and we are on a mission to accelerate digital drug discovery with the Watershed platform. Watershed enables scientists to conduct all essential analysis — from lab data to plot — with a single software platform. 

We have attracted some of the best bioinformatics, engineering, and commercial talent, and we are growing! Join a team that’s intellectually curious with a bias for action, headquartered in Cambridge, Massachusetts, composed of people who have come together to enable outcomes while empowering the research of all those committed to changing lives — all while bringing transformational change to a $40 billion industry.

Role

Watershed Informatics is hiring a Senior Software Engineer to design and build new features for our omics research platform. We’re looking for engineers eager to weigh tradeoffs, solve real problems, and expand the capabilities of an enterprise research offering. 

You’ll partner with our engineers and bioinformaticians to understand the technical limitations of our platform and the bioinformatics tools we connect to. Cloud Data Lab handles large volumes of genomic data - you’ll build services to move data between components and interfaces so biologists create better analyses. 

We are currently focused on senior level, experienced engineers. To us, this means 3-6 years of industry experience designing and writing software to solve tough problems in rigorous engineering environments. 

Responsibilities

• Develop new services and features that expand and improve how scientists analyze omics data on Cloud Data Lab.
• Meet with bioinformaticians to uncover functionality and technical requirements of current and in-development bioinformatics tools
• Design core functions scientists and users will draw on to create interoperable bioinformatics solutions. 
• Coordinate with engineers and leadership to manage and prioritize projects.

Qualifications

• 3-6 years of experience with some of the following: Python, JavaScript, RESTful APIs
• Industry experience developing complex functions for a data-driven software offering.
• Practical understanding of computer science and system design principles. 

Watershed is an equal-opportunity employer and believes diversity of all types is integral to company success. We do not discriminate on the basis of religion, sexual orientation, gender identity, race, ethnicity, national origin, marital status, veteran status, or disability status.

About Watershed

Our vision is to become the leading biocomputing platform. The future of biology is in big data analysis, and we are on a mission to accelerate digital drug discovery with the Watershed platform. Watershed enables scientists to conduct all essential analysis — from lab data to plot — with a single software platform. 

We have attracted some of the best bioinformatics, engineering, and commercial talent, and we are growing! Join a team that’s intellectually curious with a bias for action, headquartered in Cambridge, Massachusetts, composed of people who have come together to enable outcomes while empowering the research of all those committed to changing lives — all while bringing transformational change to a $40 billion industry.

Responsibilities

• Implement data exploration APIs and tools, including visualizations and
  numerical routines
• Work closely with in-house biologists and our customers to incorporate feedback
  and improvements into the codebase
• Create and maintain external documentation for APIs and tools

Qualifications

• Experience in any of the following areas: sequencing data analysis,
  bioinformatics, data visualization, or statistics
• Programming experience in Python, including experience with Pandas and
  Matplotlib
• Experience working with Unix/Linux
• Familiarity with software design patterns and best practices
• Strong problem-solving and communication skills

Watershed is an equal-opportunity employer and believes diversity of all types is integral to company success. We do not discriminate on the basis of religion, sexual orientation, gender identity, race, ethnicity, national origin, marital status, veteran status, or disability status.

About Watershed

Our vision is to become the leading biocomputing platform. The future of biology is in big data analysis, and we are on a mission to accelerate digital drug discovery with the Watershed platform. Watershed enables scientists to conduct all essential analysis — from lab data to plot — with a single software platform. 

We have attracted some of the best bioinformatics, engineering, and commercial talent, and we are growing! Join a team that’s intellectually curious with a bias for action, headquartered in Cambridge, Massachusetts, composed of people who have come together to enable outcomes while empowering the research of all those committed to changing lives — all while bringing transformational change to a $40 billion industry

Role

Watershed Informatics is hiring an experienced UI Software Engineer to design and build powerful interface features for our genomic analysis and system management software. We’re looking for engineers eager to weigh tradeoffs, solve real problems, and expand the capabilities of an enterprise software offering. 

You’ll work side-by-side with fellow engineers, bioinformaticians, and our VP to invent new ways for biologists to convert data into better plots. Focusing on developing new features with ReactJS and NextJS, you’ll consult with biologists and our bioinformaticians to understand the stages of genomic analysis, and create an interface that is exceptionally flexible and useful for scientists. 

We are currently focused on mid-senior level, experienced engineers. To us, this means 2-7 years of experience designing and writing software that solves tough problems in a rigorous engineering environment. 

Responsibilities

• Design and build web applications with the latest web technologies
• Create intuitive and well-polished user interfaces
• Work closely with a designer and engineering members to iterate on platform design and functionality
• Integrate with and implement backend API's to create new UI features

Qualifications

• Experience with some of the following: React, GraphQL, Apollo, Typescript
• Proficient with all of the following: HTML, CSS, JavaScript (ES6)
• Solid understanding of core UX and design principles
• Industry experience with building single page applications