Role Summary:

The Data Sciences team at Dyne Therapeutics is seeking an exceptional Co-Op candidate to contribute to development of machine learning (ML) and AI-driven tools for our R&D programs. The primary focus will be on refining molecular sequence-based ML models for property/activity prediction. This includes working with sequence, structural, and contextual features to enhance model performance and generalizability.

In addition, the Co-Op will contribute to development of LLM-based pipelines for scientific document drafting and evaluation, including retrieval-augmented generation (RAG) workflows to support internal research and regulatory processes.

This role provides hands-on experience at the intersection of computational biology and applied AI, directly supporting team priorities in molecular optimization, pipeline expansion, and AI capability development.

This role is based in Waltham, MA without the possibility of being remote. This is a 6-month position beginning in July.  

Candidates must be enrolled in an accredited college or university.

 
Primary Responsibilities Include: 

• Support data curation, preprocessing, and feature generation for biomolecular sequence ML models.
• Assist with model training, evaluation, and benchmarking under guidance.
• Contribute to development and testing of LLM-based document drafting and verification pipelines.
• Deliver well-documented and reproducible code, analysis summaries, and a final presentation of contributions.

 Education and Skills Requirements: 

• Undergraduate or Graduate student currently pursuing a degree in bioinformatics, Computational biology, or computer science or equivalent experience. Must be in active student status during duration of Co-Op program.
• Demonstrated competency in python and/or R programming skills.
• Prior experience in data science, AI, or machine learning is preferred.
• Strong organizational skills and solid written and oral communication ability.

#LI-Onsite

Your Impact at LILA

Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), software engineers build the systems that connect generative models, scientific data, and experimental workflows into reliable, production-grade pipelines powering Lila's protein design and engineering campaigns.

We're hiring a Staff ML Engineer, Life Sciences AI to lead software infrastructure development for our protein design and engineering pipelines. This is a senior IC role focused on the engineering systems that surround and support our ML stack — pipeline orchestration, data flow between computational and experimental systems, integration of new tools and methods, and the developer experience that lets LSAI move fast on commercial partnership deliverables.

What You'll Be Building

• Architect and build software infrastructure powering Lila's protein design and engineering pipelines: orchestration, data flow, APIs, and integration with experimental systems.
• Own the engineering side of LSAI's "Lab-in-the-Loop" lifecycle — connecting computational outputs to experimental inputs and feeding results back into design workflows.
• Onboard new tools and methods developed by AI scientists and ML engineers into production-ready systems used in commercial partnership campaigns.
• Partner cross-functionally with ML researchers, scientists, and platform engineers to translate research code into reliable, scalable systems.
• Set engineering standards for LSAI software — design reviews, CI/CD, testing, observability, reproducibility — and mentor senior engineers as the team grows.
• Diagnose and resolve reliability, performance, and scaling bottlenecks in production pipelines supporting partnership deliverables.

What You’ll Need to Succeed

• Master's degree or higher in Computer Science, Machine Learning, or a related quantitative field (or Bachelor's with equivalent professional experience).
• 8+ years of professional software engineering experience in Python (or comparable systems languages).
• Proven experience designing, building, and operating scalable production systems — APIs, data pipelines, orchestration, and cloud infrastructure.
• Strong software engineering fundamentals: system design, production-grade code, CI/CD, observability, and reliability practices.
• Experience building or operating scientific or ML-adjacent infrastructure — workflow orchestration, experiment tracking, and reproducible pipelines.
• Hands-on experience with containerization, orchestration platforms, and infrastructure-as-code on a major cloud provider.
• Track record of leading technical direction across multiple systems and partnering deeply with research scientists or ML engineers to translate scientific needs into production engineering.

Bonus Points For

• Experience building infrastructure for protein design and engineering, antibody engineering, or other molecular ML applications.
• Familiarity with biological data formats and bioinformatics tooling.
• Experience integrating ML training/inference systems with broader product or scientific platforms.
• Open-source contributions to scientific computing or data infrastructure projects.

About the Role
We are looking for an AI Scientist to join our team at the intersection of machine learning and single-cell biology. This role will focus on developing and applying foundation models to large-scale perturb-seq and single-cell datasets to uncover new biological mechanisms and therapeutic opportunities. You will help design scalable ML architectures that can extract insight from high-dimensional perturbation data and integrate across multi-omic modalities.

Key Responsibilities

• Design, train, and refine foundation models tailored to perturb-seq and other single-cell datasets.
  Build pipelines for preprocessing, normalization, and integration of large-scale single-cell and perturbation data.
• Apply ML/AI approaches to model cellular responses to perturbations and identify causal biological insights.
• Collaborate with experimental biologists to align computational methods with experimental design and discovery goals.
• Develop multimodal integration approaches across transcriptomic, epigenomic, and proteomic single-cell readouts.
• Publish methods and results in top scientific journals and present at conferences.
  
  

Qualifications

• PhD or equivalent in Computational Biology, Computer Science, Bioinformatics, or related discipline.
• Strong expertise in single-cell data analysis, particularly perturb-seq 
• Hands-on experience with foundation models or large-scale self-supervised learning (e.g., transformers, variational autoencoders).
• Strong coding skills in Python, ML frameworks (PyTorch/TensorFlow), and single-cell analysis tools (Scanpy, Seurat).
• Experience in developing scalable ML methods for large biological datasets.
  
  

Preferred

• Background in causal inference, generative models, or representation learning for biological systems.
• Familiarity with multi-omics integration and cross-modal foundation models.
• Track record of impactful publications in computational biology, machine learning, or related fields.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $150,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

Essential duties include but are not limited to:

Help streamline internal processes – work directly with the Precision leadership to improve processes and efficiency; investigate optimal research techniques and implementation strategies; update existing tools and documentation to increase adherence to best practices; support development and refinement of interactive tools that use existing real-world evidence analyses.

Support ongoing research projects – assist with literature reviews on diverse healthcare topics; help with real-world evidence studies including protocol development, data programming, and results; develop interactive summaries of real-world evidence analyses; help interpret and communicate quantitative and qualitative findings to internal and external audiences; contribute to reports, results tables, presentations or peer-reviewed manuscripts; participate in client-facing activities; provide administrative project support.

Qualifications:

Required:

• Enrolled in a public health (epidemiology, biostatistics, bioinformatics), economics, data science, life sciences, or healthcare related undergraduate, or preferably, graduate program at an academic institution at the time of recruitment.

Other required:

• Proven interest in public health, life sciences, or pharmaceutical research and analytics
• Research experience in epidemiology, public health, health services research, health policy, economics or related fields
• Foundational knowledge of epidemiologic concepts such as observational study designs, measures of association, and common sources sources of bias and confounding
• Familiarity / competency with statistical programming tool such as R, SQL, SAS or similar platform
• Ability to work effectively both individually and as part of a team
• Detail oriented with exceptional interpersonal and time management skills
• Keen interest in learning and sharing knowledge
• Strong academic record
• Proficiency with Microsoft Office

Preferred:

• Enrolled in life sciences related advanced degree program
• Strong understanding of the scientific method; formal training in quantitative methodologies
• Familiarity with interactive data visualization tools such as R Shiny, Power BI, Tableau, or equivalent platforms
• Familiarity with working in virtual AWS environment, Git, and Github

Essential duties include but are not limited to:

Help streamline internal processes – work directly with the Precision leadership to improve processes and efficiency; investigate optimal research techniques and implementation strategies; update existing tools and documentation to increase adherence to best practices; support development and refinement of interactive tools that use existing real-world evidence analyses.

Support ongoing research projects – assist with literature reviews on diverse healthcare topics; help with real-world evidence studies including protocol development, data programming, and results; develop interactive summaries of real-world evidence analyses; help interpret and communicate quantitative and qualitative findings to internal and external audiences; contribute to reports, results tables, presentations or peer-reviewed manuscripts; participate in client-facing activities; provide administrative project support.

Qualifications:

Required:

• Enrolled in a public health (epidemiology, biostatistics, bioinformatics), economics, data science, life sciences, or healthcare related undergraduate, or preferably, graduate program at an academic institution at the time of recruitment.

Other required:

• Proven interest in public health, life sciences, or pharmaceutical research and analytics
• Research experience in epidemiology, public health, health services research, health policy, economics or related fields
• Foundational knowledge of epidemiologic concepts such as observational study designs, measures of association, and common sources sources of bias and confounding
• Familiarity / competency with statistical programming tool such as R, SQL, SAS or similar platform
• Ability to work effectively both individually and as part of a team
• Detail oriented with exceptional interpersonal and time management skills
• Keen interest in learning and sharing knowledge
• Strong academic record
• Proficiency with Microsoft Office

Preferred:

• Enrolled in life sciences related advanced degree program
• Strong understanding of the scientific method; formal training in quantitative methodologies
• Familiarity with interactive data visualization tools such as R Shiny, Power BI, Tableau, or equivalent platforms
• Familiarity with working in virtual AWS environment, Git, and Github

What do we need

We are seeking a Scientific Technical Solutions Lead to join the team developing scientific Solutions built on Dotmatics LUMA, a next-generation, multi-tenant, AI-powered data management and workflow automation for multimodal scientific discovery. As a Scientific technical lead on the team, you will work closely with other Solution Architects, product management, engineering teams, and external stakeholders to deliver exceptional product capabilities via Luma Solutions.

Your focus will be on designing and implementing the configuration necessary to realise product vision and on ensuring that this configuration follows best practices within the Life Sciences and Chemical & Material space.

This role offers the opportunity to shape a foundational part of the modern lab—helping scientists work faster, smarter, and with greater impact.

In this role you will get to:

• Design configuration: Collaborate with Product to determine application structure, define entity/data models, specify task workflows (Scientific Workflows) , and define desired data visualization experiences
• Develop configuration: Create registration entities, data flows, task templates, data visualization experiences, and other configurations in support of developing Luma Solutions that will be delivered as part of the product
• Test and troubleshoot configuration: Perform in-team testing of configuration and assist is handing test cases to the QA group for release testing. Troubleshoot configuration to understand why it is not producing desired results.
• Contribute to documentation: Write draft documentation of configuration and workflows and collaborate with the Documentation team to develop final customer-facing documentation
• Train internal and external users: Train members of other Dotmatics teams and early customers on how to use Luma Solutions configuration and the workflows it supports
• Provide input into new product features: Use new product features in Luma Solutions and provide feedback on the experience, participate in user experience testing, and provide input to the Product team about features that will enable the best Solutions
• Champion quality and best practices: Actively participate in the development of best practices for Luma configuration, and ensure these best practices are followed in the development of Luma Solutions

We are looking for people who have 10+ years of hands-on experience building and delivering informatics solutions for Life Sciences customers. The ideal candidate holds a Bachelor's or advanced degree in Life Sciences, Data Science, Chemistry, Biology, Bioinformatics, or a related technical discipline — and brings a genuine passion for quality and continuous improvement, fueled by a drive to solve problems that truly matter.

The key skills we are looking for: 

• Life Science Industry experience, either as a Scientific Solution Architect, technical application Scientist or a Scientist who has been heavily involved with designing products or technical applications
• Advanced expertise in data modeling, with a proven ability to design robust, scalable data structures
• Expert-level proficiency in configuring low-code platforms and designing end-to-end workflows
• Demonstrated success delivering scientific data platforms or tools spanning data modeling, ETL, APIs, and BI/reporting
• Expert-level SQL skills, with strong working knowledge of Python and JSON
• Deep experience integrating tools and modules to architect complete, cohesive solutions
• Strong analytical ability to translate product requirements into precise technical configuration designs
• Excellent communication skills — able to distill complex technical concepts for both technical and non-technical audiences at all levels
• Experience running and/or supporting scientific workflows in a production or research environment

You may also have 

• Experience running scientific test cases
• Understanding of software testing and or SDLC
• Working knowledge of Databricks
• Drug Discovery or Biotechnology industries or Other scientific Industries

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency, and acumen of our business decisions and to empower and scale product innovations. We cover a wide area of the data spectrum, including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling, economics, and machine learning. Aligned and partnering with product groups, we use this vast tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure the impact / incrementality on our community of players, developers, and advertisers.

WHY ADVERTISING SCIENCE?

Advertising at Roblox is new, facing critical scale, effectiveness, and implementation challenges, while operating in our civility and user focused experiences. As a new strategic area, work will be innovative and impactful. Scientific rigor will be critical in success as we organize our data model, design principled measurement systems, and architect the future of incrementality measurement and actioning, to enable our communities.

In this role, you will contribute to the new Ads Science team within the broader Economy DSA team, collaborating with engineers and product managers to innovate our advertising systems and operations. Work will include data pipeline design and ownership, modeling for ad delivery and targeting, modeling for user segmentation / experimentation, and experimental design and analysis. We are early in this multi-year journey, and seek a dedicated and passionate scientist to help design this vision and execute the innovation to achieve it.

You Will:

• Design and lead offline model evaluation end-to-end (pipelines, frameworks, analysis).
• Contribute to ads ML feature and model improvements, collaborating with engineering to put these in production.
• Build offline evaluation and simulation models for our ads marketplace.
• Accelerate product development through your understanding of the underlying data and your ability to partner with product and technical leaders to provide insights.
• Lead experimental design and analysis for your ads domain.
• Design science roadmaps and experimentation agendas to determine success of product feature launches.

You Have:

• Domain experience in digital ads systems, including ownership of critical analytic or production pipelines.
• 4+ years of industry or academic experience in data science, economics, analytics, or machine learning engineering.
• Expertise in data transformation and programming, and proficiency in developing data pipelines through use of Spark, Hive, and Airflow.
• Experience with auctions and experimentation in market settings.
• Graduate education in a technical field (preferred: rigorous applied training including a graduate degree in economics, statistics, bioinformatics, cognitive science, physics, or similar).

You Are:

• Candid on relative opportunities for impact, and evidence-seeking to update beliefs.
• Passionate about Roblox’s mission to connect a billion people every day with optimism and civility, including through increasing earnings for our creator community.
• A strong communicator. You understand that analysis must be presented in meaningful ways and lead spirited discussions about the findings. You can explain technical concepts to non-technical audiences and discuss appropriate tradeoffs.
• Effective in a collaborative work environment with a track record of simplifying complex and ambiguous problems.

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Data Scientist II, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, ML) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

Our team is responsible for:

• Conducting deep-dive analysis to influence R&D decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers. 
• Building the right metrics to measure campaign health: improving campaign performance monitoring by establishing the right metric framework, and understanding cause-and-effect relationships across drivers
• Evaluating ads system health: understanding changes and drivers of our complex systems, and diagnosing issues through a set of input/output metrics of each component.

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Provide strategic thought partnership to cross-functional teams, leveraging data-driven insights to influence and guide product decisions, roadmap prioritization, and overall business strategy.
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with Product Management, Engineering stakeholders ;work effectively with cross-functional partners in a global company.
• 3+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.
• Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).

Profluent is seeking a Principal Infrastructure & Security Engineer to serve as the primary owner of Profluent’s security posture across scientific systems, lab automation environments, cloud and business infrastructure, endpoints, identity systems, and core operational workflows.

This person will be accountable for the design, implementation, operation, and continuous improvement of the technical controls, security standards, and operating practices that protect Profluent’s systems and data. This includes security architecture, access controls, hardening, monitoring, incident readiness, vendor and customer security assurance, and the systems and evidence required to achieve and maintain compliance commitments.

This is not a narrow compliance-only or infrastructure-only role. It is a broad ownership role for security across Profluent’s environments, with close partnership across Operations, Machine Learning, Bioinformatics, and Lab Automation.

Responsibilities

• Own Profluent’s overall security and compliance posture across company systems, scientific computing, lab automation, endpoints, identity, SaaS, cloud infrastructure, networking, and data-handling workflows, and be accountable for the ongoing maturity of security controls and practices across those environments
• Lead the implementation and operational maturity work required for Profluent to achieve and maintain SOC 2 and related compliance certification requirements, including control operation, evidence collection, monitoring, and repeatable processes
• Serve as the primary owner for security and compliance readiness across company systems, ensuring that Profluent can meet ongoing audit, certification, and customer assurance requirements over time 
• Own the translation of customer agreements, internal policies, and compliance requirements into concrete technical and operational controls
• Standardize and harden bioinformatics, lab informatics, and machine learning environments to align with security, reliability, and compliance requirements
• Define and drive adoption of secure baseline configurations, access controls, logging, backup practices, patching standards, and change management processes
• Own and evolve how Profluent approaches security more broadly, identifying gaps, prioritizing risks, and driving improvements beyond minimum compliance scope
• Drive standardization of Windows-based lab automation environments, balancing security, uptime, vendor constraints, and usability in laboratory settings
• Collaborate with stakeholders to document controls, system boundaries, standard operating procedures, and technical evidence needed for audits, certification efforts, and customer reviews
• Support vendor and platform evaluations related to security, observability, endpoint management, and infrastructure operations
• Improve identity, access, and account lifecycle management across company systems, including onboarding, offboarding, least-privilege access, and periodic access review support 
• Monitor key systems and respond to operational issues with an emphasis on root-cause analysis and durable remediation
• Maintain asset, system, and environment documentation so that critical processes are auditable, supportable, and repeatable

Qualifications

• Experience operating with broad ownership across infrastructure, security, and compliance in regulated, audit-conscious, or security-sensitive environments
• Experience serving as the most senior or primary security owner in a startup or scaling environment, even without a large dedicated security team
• Breadth across infrastructure security, corporate security, IAM, endpoint management, logging and monitoring, vulnerability reduction, incident response, vendor risk, and compliance
• Demonstrated ability to take ownership in ambiguous environments and set direction, not just execute within a narrowly defined specialty
• Familiarity with Windows-based lab automation systems and the realities of instrument-connected or vendor-managed environments
• Experience implementing or operating against security and compliance frameworks such as SOC 2, ISO 27001, NIST CSF, or similar
• Strong understanding of identity and access management, SSO, MFA, endpoint management, logging, patching, vulnerability reduction, and system hardening
• Ability to translate compliance and contractual data-handling requirements into concrete technical and operational controls
• Strong documentation skills, with the ability to create policies, procedures, standards, and technical runbooks that others can follow
• Experience preparing organizations for, achieving, or maintaining external compliance certifications or audit readiness
• Experience with infrastructure as code and/or configuration management tools such as Terraform, Ansible, or equivalent
• Experience administering Windows environments, preferably including systems used in laboratory, automation, manufacturing, or instrument-connected settings

Preferences (but not required)

• Familiarity with audit evidence preparation, control testing, and coordination with external auditors
• Familiarity with networking fundamentals including firewalls, routing, VLANs, NAT, VPNs, and secure remote access
• Experience influencing cross-functional teams and improving organizations mature security practices without relying on rigid bureaucracy

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

The Impact You’ll Make

As a Manager within Recursion's partnership-facing data science team, you will be at the forefront of reimagining drug discovery from first principles. You will lead a team of world-class computational biologists focused on identifying and advancing the next generation of oncology therapeutics. You will act as a "player-coach," balancing direct technical contribution with the mentorship and strategic leadership of a high-performing team. Your mission is to integrate Recursion’s massive datasets—phenomics, transcriptomics, and proteomics—to nominate novel targets, validate disease biology, and define the precision oncology strategies that ensure our medicines reach the right patients.

In this role, you will:

• Lead and Develop: Direct and mentor a team of data scientists and computational biologists, fostering a culture of scientific rigor, bold experimentation, and continuous professional growth.
• Drive Target Discovery: Lead the design and execution of analyses for target nomination and validation, using Recursion’s platform to identify novel vulnerabilities in cancer biology.
• Define Early Patient Population Strategy: Develop biomarker strategies and patient-stratification hypotheses to support programs as they progress from nomination through hit-to-lead and lead-optimization.
• Bridge the Gap: Act as a key "connector," leading your team to pilot innovative analysis methods and collaborating with platform and engineering teams to productionalize and scale these tools for organization-wide impact.
• Execute Hands-On: Maintain a 50% individual contribution (IC) load, performing complex data integration and analysis to solve "killer questions" within the oncology portfolio.
• Collaborate Cross-Functionally: Partner with biologists, medicinal chemists, and clinical leads to build compelling data packages that drive program milestones and investment decisions.
• Present data analysis to external decision makers and stakeholders in a clear and compelling way that drives toward getting medicines to patients.

The Team You’ll Join 

Our group is a bold, agile, diverse collective of computational drug discovery scientists deeply focused on the singular goal of bringing new therapeutics into the clinic at an accelerated pace. We are a computational group that spans precision oncology, I&I (immunology and inflammation), and neuroscience and focuses on advancing novel, targeted therapies for these disease areas. We partner closely with our biologists and medicinal chemists to design and execute impactful and decisional data analysis for multiple programs. We are responsible for data strategy across the portfolio and supported by computational leadership in designing scalable and reproducible experiments that serve to advance multiple programs within the portfolio. 

Our team collaborates extensively with computational biologists in other therapeutic areas (neurobiology, immunology, etc.) as well as data scientists and engineers from our core platform teams to provide a strong network of feedback and support. 

The Experience You’ll Need

• PhD in a quantitative field (Computational Biology, Bioinformatics, Statistics, Cancer Biology, etc.) with 5+ years of experience in biotech or pharma industry OR MS in a relevant field and 7+ years of experience in biotech or pharma industry solving fundamental problems in oncology or drug discovery.
• People Management Experience: Proven track record of managing and developing direct reports within a scientific or technical environment.
• Oncology Domain Expertise: Deep understanding of cancer biology, including experience with biomarker discovery and patient population stratification.
• Experience with two or more oncology areas; strong understanding of patient genetics and historical druggability of disease relevant pathways
• Deep expertise in the analysis and data integration of two or more ‘omics data modalities (phenomics, transcriptomics, proteomics, genomics), including experience working with patient data
• Exceptional data visualization skills
• Computational Proficiency: Advanced skills in Python or R for the analysis of high-dimensional biological data (e.g., transcriptomics, proteomics, or high-content imaging).
• Excellent Cross-Functional Communication: Ability to distill complex technical concepts into clear and compelling narrative for internal and external-cross functional audiences.

Nice To Have:

• Public Data Mastery: Familiarity with large-scale oncology datasets such as TCGA, CCLE, DepMap, and/or Real-World Data (RWD).
• Experimental Design: Experience designing high-throughput screens or CRISPR/small-molecule perturbations to validate therapeutic hypotheses.
• Clinical Translation: Exposure to the requirements for IND-enabling studies or clinical trial biomarker analysis

Working Location:

This is an office-based, hybrid role in either our Salt Lake City or New York City offices. Employees are expected to work in the office at least 50% of the time.

Working Location & Compensation:

This is an office-based, hybrid role and can be based in either our Salt Lake City or New York City office. Employees are expected to work in the office at least 50% of the time. At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is $151,800 to $230,000 You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. 

#LI-EP1

The Opportunity:

Universal DX is seeking an experienced Senior Biostatistician to join our growing product development team working on the development and commercialization of Next Generation Sequencing (NGS) products for early cancer detection. This role will be instrumental in the planning, development, and execution of statistical analyses for Analytical Validation (AV) studies supporting Signal-C, Universal DX’s screening test for colorectal cancer. This role will work flexibly within a matrixed organization, collaborating across multiple teams within Product Development.

You will be part of a team that is passionate about developing novel diagnostic tests for the early detection of cancers. As part of the team, you will be in a Company that aims more than to become one of the leaders in the industry. We want to have a huge positive impact on society by achieving the ambitious purpose of “making cancer a curable disease by detecting it earlier”.

How you’ll contribute:

What you’ll bring:

What we´ll offer:

Lead Product Manager, Clinical Genomics Engineering

Natera offers genetic risk assessment and diagnostic tests to patients through medical providers. The Clinical Genomics Engineering organization builds software that supports complex, regulated workflows spanning tertiary analysis workflows including variant  interpretation, clinical review, and reporting. As Natera scales across Women’s Health, Oncology, and Organ Health, delivering  cohesive, reliable, and compliant software experiences is foundational to clinical quality and commercial success.

Natera is seeking a Lead Product Manager to define and drive strategy for core components of the Results, Interpretation, and Reporting (RIR) platform. This role is responsible for shaping scalable, compliant, and cohesive clinical software systems that support complex genomics workflows across multiple business units. The Lead PM will operate as a platform-level owner, ensuring long-term architectural soundness, regulatory robustness, and measurable clinical and operational outcomes.

Initial Focus and Scope Evolution

The Lead Product Manager will lead cross-functional alignment across engineering, clinical, quality, and downstream systems to ensure RIR components operate as a cohesive, scalable platform. This role will identify systemic gaps, resolve cross-team tradeoffs, and drive architectural and workflow decisions that support long-term growth and regulatory compliance.

This role will initially own one or more RIR software components or initiatives, with responsibility for defining long-term strategy, aligning cross-component workflows, and ensuring scalable architecture across user-facing applications, data contracts, and backend services. The Lead PM will drive strategic investment decisions, establish standards for usability and reliability, and ensure systems meet evolving clinical, operational, and regulatory requirements.

As business needs evolve, this role will expand to influence and coordinate across multiple RIR components, driving cohesive workflow design, shared data standards, and platform-level scalability across Women’s Health, Oncology, and Organ Health.

Primary Responsibilities

• Define and drive multi-year product strategy and roadmap across one or more RIR components, ensuring alignment to clinical quality, regulatory requirements, and commercial scale objectives

• Influence platform-level technical direction in partnership with engineering leadership 

• Partner closely with software engineering, bioinformatics, clinical domain experts, quality, regulatory, and other product teams

• Translate business, clinical, and operational needs into clear, actionable product requirements

• Define and evolve end-to-end user workflows, including UI/UX requirements and supporting backend functionality

• Drive cross-team alignment on shared data contracts and workflow standards

• Mentor and raise the bar for product management within the RIR organization

• Own measurable improvements in clinical workflow efficiency, reliability, and operational scalability

• Establish prioritization frameworks that balance regulatory risk, clinical impact, technical scalability, and business outcomes across RIR investments.

• Develop and track quantitative metrics related to usability, performance, reliability, and adoption

• Lead delivery teams with clear strategic direction, ensuring requirements reflect long-term platform goals, validation readiness, and system interoperability.

• Proactively identify systemic risks, architectural constraints, and workflow inefficiencies that may limit scale or regulatory robustness, and lead cross-functional initiatives to resolve them

• Partner with Quality and Regulatory leadership to shape validation strategy, risk classification, traceability, and audit readiness for RIR software systems.

• Create clear, data-driven written proposals and presentations to support stakeholder alignment and decision-making

• Act as a subject matter expert for owned components, supporting design, testing, validation, rollout, and ongoing use

Qualifications

Required

• Bachelor’s degree in life sciences, engineering, computer science, statistics, or equivalent experience

• 7+ years of experience in software product management, including ownership of complex, multi-team or platform-level initiatives

• 5+ years experience working on production software in healthcare, clinical genomics, or other regulated lifesciences domains, with demonstrated impact on validation, compliance, and system scalability

• Demonstrated experience influencing engineering architecture and long-term technical investment decisions

• Proven ability to drive alignment across highly matrixed organizations without direct authority
  Track record of independently operating in ambiguous environments and establishing product direction
  

Preferred

• Experience with clinical genomics and variant processing and interpretation workflows

• Experience owning user-facing applications, tools, or operational software

• Familiarity working with backend services, APIs, or data-driven systems

Knowledge, Skills, and Abilities

• Ability to operate effectively at both tactical and strategic levels, connecting detailed execution to broader platform vision.

• Strong analytical skills with attention to quality, reliability, and user outcomes

• Leads technical design discussions and critically evaluates architectural tradeoffs to ensure scalability, reliability, and regulatory integrity

• Proven ability to influence without authority and drive alignment across teams

• Clear, concise written and verbal communication skills across technical and non-technical audiences

• Ability to manage multiple initiatives in a fast-paced, regulated environment

• Familiarity with Next Generation Sequencing concepts is beneficial

We’re looking for a Senior Software Engineer to help design, build, and scale Profluent’s data platform. This platform houses data from protein engineering campaigns, including protein designs, experimental results, partner datasets, analytical outputs, and model-ready training data. It enables rapid machine learning, biological discovery, and secure collaboration across internal and external programs.

This role is ideal for an engineer who enjoys building robust data systems: secure ingestion pipelines, well-structured warehouses, reliable data models, access controls, auditability, and infrastructure that makes complex scientific data usable at scale. You will work closely with ML, bioinformatics, and program teams to ensure Profluent’s data is organized, governed, accessible, and protected.

Responsibilities

• Design, build, and maintain scalable data infrastructure for protein engineering campaigns, including ingestion, transformation, validation, storage, and retrieval of large scientific datasets
• Develop secure data pipelines for internal and partner-generated data, with strong attention to access control, data siloing, provenance, auditability, and compliance with data use restrictions
• Own core components of Profluent’s data warehouse and data platform, using Python, GCP, PostgreSQL, BigQuery, and related cloud-native technologies
• Build systems that transform raw experimental, computational, and partner data into structured, reliable, analysis-ready and model-ready datasets
• Establish best practices for data modeling, metadata management, data quality checks, schema evolution, versioning, and documentation
• Collaborate with ML engineers, computational biologists, data scientists, and program stakeholders to understand data requirements and translate them into scalable technical systems
• Improve engineering quality through thoughtful system design, code review, testing, CI/CD, observability, and maintainable development workflows
• Contribute to architectural decisions for how Profluent stores, secures, organizes, and uses data across programs and partnerships

Qualifications

• 5+ years of software engineering, data engineering, or data platform experience
• Strong proficiency in Python and modern software development practices, including git, testing, code review, CI/CD, and production deployment
• Experience designing and operating production data pipelines, data warehouses, and data models at scale
• Hands-on experience with cloud platforms, preferably GCP, and technologies such as BigQuery, PostgreSQL, object storage, workflow orchestration, and containerized services
• Strong understanding of data security, access control, data partitioning or siloing, audit logging, and managing sensitive or restricted datasets
• Experience working with complex, heterogeneous datasets and building systems that make them reliable, discoverable, and usable
• Ability to work independently, make sound technical decisions, and drive projects from ambiguous requirements to production systems
• BS, MS, or PhD in Computer Science, Engineering, Data Science, Bioinformatics, or a related technical field, or equivalent practical experience

Preferences (but not required)

• Experience with scientific, biological, clinical, genomic, laboratory, or high-throughput experimental data
• Experience managing external partner, customer, or restricted-access datasets
• Familiarity with data governance, lineage, metadata systems, schema registries, or data catalogs
• Experience with research data systems, LIMS, ELNs, Benchling, or adjacent scientific platforms
• Background working with ML, data science, computational biology, or cross-disciplinary technical teams
• Interest in learning biology, gene editing, protein design, or machine learning concepts

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

We’re looking for a hands-on engineering manager to lead Profluent’s Lab Informatics Platform team. This team builds the systems scientists use to design experiments, track samples, capture assay data, integrate with Benchling and lab automation, and make experimental data usable for analysis and machine learning.

The ideal candidate is both an experienced people manager and a strong technical lead. You’ll formally manage and mentor a small team while remaining deeply involved in architecture, data modeling, database design, and technical execution. You’ll work closely with wet-lab scientists, automation engineers, data scientists, and ML experts to build practical, scientist-facing tools that make complex experimental workflows scalable, traceable, and actionable.

Responsibilities 

• Lead, mentor, and grow a software engineering team focused on lab informatics systems, scientific data infrastructure, and scientist-facing applications
• Architect and deliver the roadmap for systems that support sample tracking, assay data capture, Benchling integration, lab automation, experimental metadata, and analysis workflows
• Design robust data models for protein engineering and gene editing experiments, including constructs, samples, reagents, cell systems, assay results, metadata, and experimental lineage across mammalian and bacterial workflows
• Partner closely with scientists to translate complex laboratory requirements into scalable software solutions that accelerate Profluent’s design-build-test-learn cycle
• Build and maintain backend systems, APIs, databases, data pipelines, and web applications using technologies such as Python, Django, PostgreSQL, BigQuery, GCP, and modern development workflows
• Establish strong engineering practices across architecture, code review, testing, CI/CD, documentation, and agile delivery

Qualifications 

• 7+ years of software engineering experience, including at least 2 years managing or leading engineers
• BS, MS, or PhD in Computer Science, Bioinformatics, Computational Biology, Engineering, or a related field, or equivalent experience
• Strong technical leadership skills, with a track record of architecting and delivering production-quality software systems
• Proficiency with Python, backend development, databases, APIs, and modern software engineering workflows
• Experience building lab informatics systems, scientific data platforms, LIMS/ELN integrations, research software, or scientist-facing applications
• Experience with data modeling and database design for complex scientific, operational, or experimental workflows
• Demonstrated ability to work closely with scientists and translate ambiguous laboratory workflows into reliable software systems

Preferences (but not required)

• Experience with Benchling, lab automation, instrument data ingestion, sample tracking, or high-throughput experimental data
• Experience with data generated from mammalian or bacterial cell systems, gene editing, protein engineering, or related biological workflows
• Frontend web development experience and interest in building intuitive scientist-facing user interfaces

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description:

Calico is seeking a machine learning scientist to join a research group investigating how genome sequence determines regulatory function and how dysregulation of these programs drives aging. We develop sequence-based deep learning models that predict gene expression, chromatin accessibility, and other functional readouts directly from DNA. We use these models to interpret human genetic variation, map causal regulatory mechanisms, and identify promising intervention points.

This work builds on a sustained research program at the intersection of deep learning and regulatory genomics, including:

• Avsec, Ž. et al. Effective gene expression prediction from sequence by integrating long-range interactions. Nat Methods 18, 1196–1203 (2021).
• Yuan, H. & Kelley, D. R. scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks. Nat Methods 19, 1088–1096 (2022).
• Linder, J., Srivastava, D., Yuan, H., Agarwal, V. & Kelley, D. R. Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation. Nature Genetics (2025).

Additional research can be found here.

Position Responsibilities:

• Design and train deep learning models for biological sequence analysis, with emphasis on gene regulation, single-cell genomics, and variant interpretation
• Partner with experimental scientists to connect model predictions to biological mechanisms — designing validation experiments, analyzing large-scale genomics data, and translating computational findings into actionable biological insights
• Communicate research through publications, open-source software, and public-facing tools

Position Requirements:

PhD in computational biology, bioinformatics, computer science, or a related field, and 0-5 years (for Scientist level) or 5+ years (for Senior Scientist level) of additional training in an industry or academic setting, with a strong publication record

• Deep expertise in machine learning with solid grounding in algorithms, data structures, and statistics
• Substantive knowledge of molecular biology and genetics; familiarity with genomic data types and public data resources
• Hands-on experience analyzing genomics sequencing data, ideally including single-cell assays
• Fluency with modern AI-assisted development and research tools (e.g., LLM-based coding assistants, literature synthesis), with a habit of proactively integrating new tools to accelerate scientific workflows
• A collaborative disposition, strong follow-through, and comfort working at the interface of computation and experiment
• Must be willing to work onsite at least four days per week

The estimated base salary range for this role is $170,000 - $233,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses

About Arc Institute

Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.

Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.

Our two Institute Initiatives reflect this model in action:

• Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets,  accelerating the path from biological insight to clinical trials.
• Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.

About the Position

We are searching for an exceptional scientific leader to establish a new team within Arc Institute’s Computational Technology Center, serving as the Director, Machine Learning for our Alzheimer's Disease Initiative (ADI). 

This ambitious initiative spans Arc's Technology Centers and Core Investigator Laboratories and focuses on high-throughput interrogation of neurodegeneration and Alzheimer's disease mechanisms using advanced gene editing and functional genomics approaches. As the Machine Learning Research Lead, ADI, you will spearhead development of sophisticated machine learning foundation models to capture cell states and infer gene regulatory networks and causal relationships to predict therapeutic interventions.

This position offers the rare opportunity to build and lead a world-class team while making direct contributions to understanding and potentially treating Alzheimer's disease through state-of-the-art computational biology and machine learning approaches.

About You

• You are passionate about machine learning and computational biology, with expertise in applying cutting edge ML approaches to biological systems
• You excel at developing interpretable machine learning approaches, such as variational inference and causal modeling methods
• You are excited about building and leading a technical team while remaining hands-on with foundation model development and implementation. 
• You thrive in collaborative, multidisciplinary environments and enjoy working with both computational scientists and wet lab biologists
• You are a continuous learner who stays current with the latest developments, in both machine learning and neuroscience

In This Position, You Will

• Attract, build and lead a team of exceptional machine learning research scientists dedicated to developing foundation models for cellular systems in Alzheimer's disease
• Develop and execute on a roadmap of interpretable machine learning approaches to understand disease mechanisms, with emphasis on variational inference, causal modeling, as well as modern transformer- and diffusion-based architectures
• Work closely with experimentalists on brain organoid/spheroid cellular models as well as in vivo models, working with scRNA-seq, Perturb-seq and other datasets to unravel causal gene pathways relevant to Alzheimer’s disease
• Develop predictive modeling approaches to identify how perturbations can move cell states from high risk Alzheimer’s profiles back to healthy / low risk states
• Collaborate closely with experimental biologists to ensure ML models are grounded in disease biology and can feedback into future experimental strategies
• Foster collaborations with external partners in the computational biology and neuroscience communities
• Publish high-impact research through preprints, journal publications, open source code, and presentations at leading conferences

Required Qualifications

• PhD in Computational Biology, Bioinformatics, Machine Learning, Computer Science, or related quantitative field
• 7+ years of relevant experience with a minimum of 3 years of people management experience
• Strong research background with experience in academic settings (university, research institute) and/or biotech/pharmaceutical industry with a focus on scientific innovation
• Proven expertise in machine learning applications to biological datasets, with specific experience in single-cell profiling data and foundation model development
• Deep experience with interpretable machine learning approaches for biological systems (e.g. variational inference methods).
• Advanced technical skills in machine learning frameworks, particularly PyTorch, and ideally experience with model training at scale
• Publications in top-tier journals in computational biology and machine learning
• Excellent communication skills with ability to present complex machine learning concepts to both computational and biological audiences
• Proven ability to remain technically hands-on while providing effective team leadership, mentorship, and management
• Background in neurodegeneration research including familiarity with Alzheimer's disease datasets, pathways, networks, disease mechanisms, and eQTL analysis is a plus 

The base salary range for this position is $380,000-$420,000. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

About Arc Institute

Arc Institute is an independent nonprofit research organization at the interface of artificial intelligence and biology, working to accelerate scientific progress and understand the root causes of complex diseases. Founded in 2021 and based in Palo Alto, Arc partners with Stanford University, UC Berkeley, and UC San Francisco.

Unlike academia, our scientists have long-term funding and industry-like resources. Unlike industry, they're free to pursue high-risk, long-term research without commercial pressures. Arc's Technology Centers and Core Investigator labs work side by side, integrating experimental and computational biology under one roof to tackle problems neither could solve alone.

Our two Institute Initiatives reflect this model in action:

• Virtual Cell Initiative: Building a full-stack virtual cell model to identify disease mechanisms and nominate drug targets,  accelerating the path from biological insight to clinical trials.
• Alzheimer's Disease Initiative: Mapping the genes, pathways, and environmental factors behind Alzheimer's disease to develop drug candidates that address root causes.

More than 300 Arconauts work together at our Palo Alto headquarters, backed by substantial long-term philanthropic funding.

Why this position could be the best job you’ve ever had?

• Work at the center of AIxBio with the potential to revolutionize drug discovery for the world.
• Work in a unique environment that incorporates both wet lab data generation and frontier AI modelling in an active learning loop.
• Join a new type of research org that fuses high-velocity execution of a startup with the intellectual rigor of a world-class academic institute, with a long runway to tackle some of the hardest - and highest potential -  challenges in science today.
• Collaborate with some of the most accomplished scientists and entrepreneurs in the world.

About the position

We are searching for an innovative scientific leader experienced in building predictive models based on single-cell genomic data. The chosen candidate will spearhead the development and application of advanced machine learning models tailored for perturbative gene expression modeling, in the context of Arc’s virtual cell initiative.

About you

• You are passionate about machine learning, ideally with experience or strong interest in biology and single-cell genomics.
• You want to develop highly innovative and accurate biology-inspired multimodal machine learning models.
• You are excited about collaborating with a multidisciplinary team of computational and experimental biologists at Arc.
• You are a strong communicator, capable of translating complex technical concepts at the intersection of machine learning and biology.
• You are a continuous learner.
• You are interested in recruiting and managing your own group of scientists and engineers as well as mentoring and training for other scientists.

In this position you will

• Lead/build a team of 6 ML research scientists and engineers augmented with undergrad/masters/PhD students to contribute to the development of a state-of-the-art foundation model and agentic framework for understanding how cells respond to perturbations.
• Work in an active learning loop with Arc’s wet lab scientists to shape the world's largest and most diverse set of single cell training data across many cell contexts.
• Collaborate closely with other research groups to integrate genomics, functional track,and omics data more broadly beyond scRNA-seq data and Perturb-seq
• Stay up to date on the latest in frontier ML research and pioneer new architectures and approaches.
• The ultimate goal is to build a high utility virtual cell model for use by biologists worldwide. We publish our breakthroughs to widely accelerate scientific progress and partner with some of the biggest names in AI.
• Commit to a collaborative and inclusive team environment, sharing expertise and mentoring others. 
• Attract the very best talent in the world to support VCI initiative goals

Requirements

• PhD in Computational Biology, Bioinformatics, Machine Learning, or a related field.
• Minimum of 5 years of experience working in/with machine learning, well versed in frameworks such as Pytorch, TensorFlow, JAX, etc.
• Proven experience leading research teams in a fast paced, multi-disciplinary environment.
• Experience with or strong interest in biology with ability to communicate and collaborate successfully with biologists and pure ML engineers.
• Excellent communication skills, both written and verbal, with a strong track record of presentations and publications.

The base salary range for this position is $380,000-$420,000. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.

About this opportunity:

At Freenome, we are seeking a Senior Software Engineer II to join our innovative Engineering team. The ideal candidate is an experienced backend engineer with a strong background in developing scalable and reliable software solutions. You will play a crucial role in designing, building, and maintaining backend services that support our mission to detect cancer early. This position requires a collaborative mindset, as you will work closely with an interdisciplinary team of engineers, scientists, and product managers to deliver high-quality software solutions. You are passionate about software development best practices and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to our engineering management team. This role will be a Remote role. 

What you’ll do:

• Design, develop, and deploy reliable, maintainable, scalable, and fault-tolerant backend services that power both our internal and external systems.
• Collaborate with interdisciplinary teams, including scientists, product managers, and other engineers, to solve complex problems and deliver high-quality software solutions.
• Mentor and guide junior engineers, fostering their growth and enhancing the team's technical expertise.
• Lead code and design reviews, champion engineering best practices and promote a culture of quality and collaboration.
• Contribute to the development of data infrastructure for machine learning applications, ensuring efficient data processing and integration.
• Drive the implementation of engineering hygiene practices, ensuring the reliability and maintainability of our systems.
• Advocate for and implement innovative software development methodologies and tools to improve team efficiency and product quality.
  

Must haves:

• Bachelor of Science in Computer Science, Engineering, or related field or equivalent training, fellowship, and/or work experience.
• At least 8 years of experience as part of a software development team successfully shipping software products, including leading projects from end-to-end and mentoring others.
• Proficiency in Python and experience with backend development in a team production environment.
• Strong experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud Platform.
• Proven experience in designing and implementing scalable backend systems, with a focus on reliability and performance.
• Excellent written and verbal communication skills, with a mindful and transparent approach to collaboration.
  

Nice to haves:

• Understanding of statistical and machine learning methods, with practical experience in applying them to real-world problems.
• Expertise in developing ETL or data pipelines that run at scale, utilizing common workflow management systems like Flyte, Airflow, or similar.
• Domain-specific experience in computational biology, genomics, bioinformatics, or a related field.
• Experience working in an FDA regulated environment, with a strong understanding of compliance requirements and best practices.
  

Benefits and additional information:

The US target range of our base salary for new hires is $161,925 - $227,325. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-REMOTE

The Opportunity

We are looking for a meticulous and detail-oriented Biology Data Quality Engineer to ensure the integrity and usability of the various and complex datasets that are central to our mission. In this critical role, you'll leverage your expertise in biology, data science, and machine learning to ensure the quality and consistency of biological data used to train and evaluate our foundation models. You'll work in collaboration with the R&D team and our engineers, using your skills to ensure our data meets the highest standards.

What You'll Be Doing

As a Biology Data Quality Engineer, you will own the following tasks:

• Data Validation Pipeline Development: Develop and implement comprehensive data validation protocols for diverse biological datasets (histology, omics, clinical). Ensure data integrity, consistency, and accuracy through rigorous quality checks. Design and implement automated data quality pipelines to streamline data validation and identify potential issues early in the data processing workflow.
• Data Curation & Standardization: Establish and enforce data standardization practices to facilitate seamless integration and analysis across different data types. Curate datasets to enhance their usability for machine learning.
• Collaboration & Communication: Work closely with the R&D team to understand data requirements and address data quality concerns. Communicate data quality findings and recommendations effectively to technical and non-technical stakeholders. Communicate and synchronize with external data providers.
• Documentation & Reporting: Maintain a detailed documentation of the data-quality assessment procedures, validation results, and data specifications. Generate regular reports on data quality metrics and trends.
• Data Source Evaluation: Evaluate and validate external public data sources, ensuring they meet our quality standards and are suitable for inclusion in our foundation model training.
• Continuous Improvement: Stay up-to-date with the latest data quality best practices and tools in the biological domain. Propose and implement improvements to our data- quality assessment processes and pipelines.

What You'll Bring

The successful candidate will have a ‘team-first’ kind of attitude; be independent, curious, and detail-oriented; thrive in a dynamic, fast-paced environment; and be fun to work with. We value individuals who bring strong domain expertise in biology alongside strong computational, hands-on skills.

• Omics Data Expertise. Deep understanding of transcriptomics data types (bulk, single-cell, spatial) and their specific quality considerations. Good knowledge of genomics and proteomics data.
• Data Quality Management: Proven experience in implementing data quality control procedures and pipelines. Familiarity with data validation tools and techniques.
• Analytical Skills: Strong analytical and problem-solving skills to identify and resolve data quality issues.
• Programming & Data Analysis: Proficiency in Python, good knowledge of data visualization libraries (e.g. matplotlib).
• Communication Skills: Excellent written and verbal communication skills to effectively convey data quality findings and recommendations.
• Educational Background: MSc in Biology, Computational Biology, Bioinformatics.

How to Stand Out:

• Computational Pathology Data Expertise: Experience in machine learning analysis of histology images.
• Cloud expertise: Experience working with AWS.
• Data Annotation Experience: Experience with developing and implementing data annotation guidelines and processes. Experience with data ontologies.
• Proven experience building or contributing to large-scale data collections (e.g. Human Cell Atlas).
• Spatial alignment of multimodal datasets (e.g. alignment between different imaging modalities)

The Candidate Journey

To be considered, please submit your CV in English. We believe in a transparent and collaborative interview process. Here is what you can expect after submitting your application:

1. Screening: Once you have applied, the hiring team will review your application to determine if your work experience and skills align with the necessary proficiencies of this position.
2. Technical Assessment: Given the technical nature of the role, you will be expected to complete a short set of Python exercises in a dedicated platform to assess your proficiency.
3. Interviews:
   • Data Curation Project: The hiring team will have an introductory call with you to share expectations for the role and to provide you with a Data Curation assignment. This assignment covers one or more key data modalities and consists of the submission of Python code and a detailed report about your work. You will get to present your work to the team, and have an interview to explore your knowledge on data modalities and relevant technical artefacts.
   • Team Fit: The hiring team will have a call with you to discuss your motivations, expectations for the role, and an overall Q&A based on your CV and previous experiences.
4. Offer: Following the completion of the interviews, our hiring team will make a final decision and will be in touch to share the outcome of your interviews. If the team would like to move forward, the recruiter will discuss the details of our proposed offer with you.
5. Onboarding: We are happy to have you joining the team. Once you have accepted and signed your offer, we will be in touch to begin the process of onboarding you to Bioptimus.

Why This is a Unique Opportunity

• Be part of a trailblazing team working at the intersection of AI, biotech, and biomedical research.
• Take on a high-impact leadership role, shaping the future of biomedical AI through strategic data partnerships.
• Work in a collaborative, innovation-driven environment with top researchers and industry experts.
  
  

About the Role:

Stylus Medicine is seeking an intellectually curious and creative Director, who will serve as a key scientific leader on our Platform team, owning the computational strategy that drives large serine recombinase (LSR) engineering and clinical translation. This role sits at the intersection of protein engineering, multi-omics analysis, and AI/ML-driven design and will lead a high-impact team spanning NGS and computational biology while driving the analytical infrastructure and predictive capabilities needed to advance our proprietary LSR platform from discovery through translation.

Key Responsibilities & Accountabilities:

• Lead and develop a team of NGS and computational biology scientists, setting technical direction, mentoring team members, and fostering a collaborative, high-performance culture
• Lead computational efforts to design and optimize LSRs and related genome engineering proteins for genetic medicine applications, integrating sequence-function, structure-function, and protein-DNA interaction datasets to guide engineering campaigns
• Lead analysis of NGS data from LSR experiments — including amplicon sequencing, WGS, hybrid capture, and long-read sequencing — to quantify on-target efficiency and genome-wide specificity
• Build, apply, and critically evaluate predictive and generative models for protein variant and library design — including rigorous benchmarking of AI/ML approaches such as protein language models, structure prediction tools, and generative design frameworks
• Integrate proprietary screening data with public evolutionary and structural datasets to prioritize variants and identify engineering levers for activity, specificity, and developability
• Oversee the design, implementation, and deployment of robust, scalable computational pipelines for multi-omics data analysis, ensuring accuracy, reproducibility, and maintainability
• Provide scientific input into platform strategy, translating computational insights into actionable directions for the broader team
• Partner closely with the Screening, Genome Engineering, and NGS teams to design experiments, interpret complex datasets, and refine engineering hypotheses
• Contribute to patent filings, regulatory submissions, and publications

Qualifications & Skills:

• PhD in Computational Biology, Bioinformatics, Protein Engineering, Machine Learning or a related quantitative discipline, with 10+ years or Master’s with 14+ years of industry experience
• Demonstrated research in protein modeling, protein design, or computational biology through publications, preprints, or equivalent industry contributions
• Hands-on experience applying AI/ML methods to protein variant and library design, including protein language models, structure prediction, and generative design approaches (e.g., AlphaFold2/3, RFdiffusion, ProteinMPNN, ESM)
• Expert-level proficiency in Python and/or R, with deep familiarity with data science libraries (e.g., Pandas, NumPy, Bioconductor, SciPy, PyTorch, or JAX)
• Experience with cloud computing platforms and workflow management systems
• Excellent communication and documentation skills, with a track record of effective collaboration in fast-paced, interdisciplinary environments

Pay Range; $245,000 - $265,000

Based in Fremont, California, Personalis is a genome-oriented diagnostics company pioneering new paradigms in cancer management. We transform patient care through genomic characterization of tumors and ultrasensitive detection of disease recurrence or progression.  To achieve this, we leverage whole-genome, exome, and bespoke targeted sequencing with proprietary algorithms to provide unmatched genetic accuracy.

Join a world-class, multidisciplinary team to drive impactful R&D projects to improve our cutting-edge clinical offerings. Your work will advance a new generation of precision medicine products used by global biopharma and clinicians to transform cancer diagnostics and therapeutics.

Responsibilities:

• Organize and help perform internal proof of principle projects, development projects, and verification and validation exercises for liquid biopsy products in the Personalis portfolio.
• Work with the broader R&D organization to scope, track and troubleshoot liquid biopsy projects with internal and external collaborators and customers.
• Collaborate with process development, tech transfer, and operations teams to shepherd early stage products, product revisions, and early projects through to operations.
• Work with bioinformatics teams to plan experiments and analyze results.
• Identify problems in current processes and come up with troubleshooting approaches and
• Participate in meetings and present results.
• Use effective two-way communication to create and maintain a collaborative working environment.
• Support and ensure compliance with all department and company policies and procedures.

Education and Experience:

• Ph.D or MS with a minimum of 8 or 12 years of experience.
• Minimum of 2 years of laboratory experience in NGS and/or liquid biopsy focused molecular biology.
• Solid understanding of DNA/RNA manipulation.
• Excellent organization, documentation and communication skills.
• Passion for exploring new assays, hands-on experiment execution and creative thinking to solve problems.
• Excellent ability to multitask and troubleshoot complex protocols.
• Experience with automation (Hamilton or other liquid handlers) helpful.
• ISO13485 validation experience helpful.
• Data analysis skills with experience in Excel, JMP, R or Python.
• Prior experience working with a LIMS directed environment.
• Prior experience in cancer biology is strongly desired.

The hiring range for this position is $170,000 to $200,000 per year, which may factor in various geographic regions. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. Our full-time regular positions also include an annual performance-based bonus (or a sales incentive plan) and long-term incentive units (equity) provided as part of our compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Personalis is an equal opportunity employer and is committed to the full inclusion of all individuals. As part of this commitment, Personalis will ensure that persons with disabilities are provided with reasonable accommodations. If you need an accommodation to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please let your recruiter know, if/when they contacts you.

Protecting Our Candidates: At Personalis, we value your security. Please note that all official correspondence from our team will come exclusively from @personalis.com email addresses. We will never ask for personal financial information or conduct interviews over text or chat platforms. If you receive a suspicious request, it is likely a scam. We are committed to a safe recruitment experience and actively work with authorities to investigate and prosecute cyber crimes targeting our community.

Personalis is an Equal Opportunity Employer/Minorities/Females/Veterans/Disabilities. Personalis offers a competitive compensation package and benefits including medical, dental, vision, 401(k) match, ESPP, tuition reimbursement, sick/vacation time, commuter benefits/ EV charging stations, onsite gym, and wellness benefits. (For US only, benefits in other countries may vary.) 

#LI-KK1 #LI-Onsite

Personalis is a genome-scale diagnostics company with a mission to pioneer genome guided medicine. Our priority is to obtain the most accurate genetic data from each sample, and then to draw the most reliable medically-focused conclusions from these. Our tests are based on whole human genome and exome sequencing, conducted in our state-of-the art laboratory.  We analyze results utilizing proprietary databases, advanced human reference sequences, and sophisticated algorithms. Personalis is based in Fremont, California.

Summary:

We are looking for a dynamic and experienced Senior Director of Advanced Technologies to lead a team in scoping, evaluating, and implementing cutting-edge advancements in sequencing, sample preparation and new assay creation. This role will drive innovation in our proprietary technologies, enhancing performance and expanding capabilities. Your contributions will play a key role in shaping the next generation of genomics-based precision medicine products, supporting immuno-oncology, cancer clinical trials, diagnostics, and therapeutics used by pharma, biotech, hospitals, and clinicians.

Responsibilities:

• Develop and execute the advanced technology strategy, ensuring alignment with company objectives and long-term vision.
• Lead efforts to evaluate and integrate new technologies that expand and improve Personalis products.
• Participate in forward-looking strategic planning and influence company-wide technology adoption.
• Identify new initiatives and build consensus across various stakeholder groups with clear success measures.
• Work closely with bioinformatics teams to design experiments and validate new procedures and analytics.
• Partner with the operations teams to ensure the smooth adoption of new technologies.
• Collaborate across functions to troubleshoot issues and implement solutions that drive efficiency.
• Influence company policy and strategy by partnering executive leadership.
• Recruit, mentor, and manage a high-performing team of scientists to drive innovation and operational excellence.
• Foster a culture of continuous learning, inclusion, and professional growth for all team members.
• Ensure accountability for results and provide strategic focus to support both short- and long-term organizational success.
• Demonstrate strong leadership, communication, and influence across all levels of the organization.
• Model and promote Personalis values, fostering collaboration and valuing diversity.
• Drive continuous innovation by encouraging the team to identify process efficiencies and new solutions.
• Support compliance with all department and company policies, ensuring regulatory and quality adherence.
• Work cooperatively across functions to achieve broader company objectives and business success.

Education & Experience:

• Ph.D in a related field with 10+ years of relevant experience, preferably in molecular biology.
• Minimum of 5 years of management experience, with a proven ability to set a clear vision, establish expectations, and motivate teams to achieve results.
• Demonstrated success in driving performance, achieving objectives, and leading teams to meet departmental goals.
• Strong communication, presentation, and influencing skills, with the ability to effectively engage and gain support from senior leadership.
• Expertise in strategic thinking, decision-making, and negotiation, ensuring smooth daily business operations.

The hiring range for this position is $240,000 to $285,000 per year, which may factor in various geographic regions. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. Our full-time regular positions also include an annual performance-based bonus (or a sales incentive plan) and long-term incentive units (equity) provided as part of our compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Personalis is an equal opportunity employer and is committed to the full inclusion of all individuals. As part of this commitment, Personalis will ensure that persons with disabilities are provided with reasonable accommodations. If you need an accommodation to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please let your recruiter know, if/when they contacts you.

Protecting Our Candidates: At Personalis, we value your security. Please note that all official correspondence from our team will come exclusively from @personalis.com email addresses. We will never ask for personal financial information or conduct interviews over text or chat platforms. If you receive a suspicious request, it is likely a scam. We are committed to a safe recruitment experience and actively work with authorities to investigate and prosecute cyber crimes targeting our community.

Personalis is an Equal Opportunity Employer/Minorities/Females/Veterans/Disabilities. Personalis offers a competitive compensation package and benefits including medical, dental, vision, 401(k) match, ESPP, tuition reimbursement, sick/vacation time, commuter benefits/ EV charging stations, onsite gym, and wellness benefits. (For US only, benefits in other countries may vary.) 

#LI-KK1 #LI-Onsite

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 SUMMARY:

Join Natera’s Oncology Product Development team as a Scientist focusing on Assay Development. You will build, validate, and troubleshoot next-generation sequencing (NGS) and cell-free DNA (cfDNA) assays used in liquid biopsy and Minimal Residual Disease (MRD) testing. Every sample represents a real person, and your work will directly impact patient care by ensuring our assays meet strict clinical diagnostic standards.

PRIMARY RESPONSIBILITIES:

• Design development, verification, and validation studies using stakeholder input, driving milestones to completion within established timelines
• Integrate automated workflows with digital tracking systems, including Laboratory Information Management Systems (LIMS) such as LabVantage, and execute integration testing
• Think team by partnering directly with biostatistics, bioinformatics, and lab operations to root-cause issues using data, communicating clearly without translation layers
• Plan and execute moderate to high complexity experiments, and perform primary data analysis using tools like Excel and JMP
• Provide unvarnished, data-backed updates at project and departmental meetings regarding progress, outcomes, and next steps
• Author clear Standard Operating Procedures (SOPs), study reports, and transfer documents for production implementation
• Train team members on new SOPs and automated workflows, and provide troubleshooting support to lab operations
• Adapt to evolving science and operational needs, taking ownership of tasks that move the work forward

QUALIFICATIONS:

• Ph.D. with a minimum of 2 years of industry experience, or a Master's degree with a minimum of 5 years of industry experience

KNOWLEDGE, SKILLS, AND ABILITIES:

• Deep technical understanding of chemistry underlying nucleic acid extraction, PCR, NGS library preparation, and hybrid capture technologies
• Ability to independently design experiments, interpret data, and determine the next scientific step
• Extensive hands-on experience with molecular biology techniques, specifically NGS, PCR/qPCR, and nucleic acid extraction and quantification
• Experience building automated workflows and executing Laboratory Developed Tests (LDT) under CLIA/CAP guidelines is highly desired
• Ability to manage multiple priorities while operating with pace and precision
• Clear, direct communication and presentation skills with strict attention to detail
• An ownership mindset that identifies gaps, tests assumptions with data, and executes without waiting for a finished playbook
• Proven ability to author clear, precise project plans, study protocols, reports, and SOPs

Natera is seeking a highly skilled and innovative Staff Scientist to join our Molecular Biology Research Team. The Staff Scientist will conduct new product research to develop/refine methylation-based next-generation sequencing (NGS) technologies that advance Natera’s oncology diagnostic capabilities. In this role, you will independently lead projects to design, prototype, and optimize novel NGS methods and collaborate cross-functionally to move concepts from ideation to implementation. A successful candidate must have a strong background in molecular biology and/or chemistry, substantial experience with NGS-based methylation detection, and a track record of successful research leadership in an industrial setting.

Primary Responsibilities:

• Lead and manage the development of innovative NGS-based diagnostic assays from feasibility through optimization.

• Define project goals and plans with input from stakeholders and manage multiple project streams in parallel.

• Independently design and execute complex laboratory experiments; analyze and interpret results to guide research direction.

• Coordinate cross-functional efforts to meet milestones and collaborate closely with bioinformatics, statistics, and data science teams to ensure robust experimental design and data analysis.

• Mentor and guide junior scientists while promoting scientific rigor and best practices.

• Author high-quality protocols, technical reports, and study documentation.

• Communicate progress regularly to stakeholders, including departmental meetings and senior leadership.

• Contribute to risk management, strategy development, and continuous improvement of scientific workflows.

Qualifications:

• Ph.D. in molecular biology, genomics, or a closely related field.

• Minimum 8 years of relevant industry experience, or 2+ years postdoctoral research with 6+ years in industry.

• Proven experience in designing and advancing NGS-based diagnostics, preferably in the field of oncology.

Knowledge, Skills, and Abilities:

• Extensive hands-on experience with NGS platforms, including sample prep, library prep, target enrichment (e.g., multiplex PCR, hybrid capture), and sequencing.

• Strong understanding of molecular biology techniques related to DNA/RNA manipulation and epigenomics/methylation detection.

• Proficient in statistical analysis tools such as Excel, JMP, R, or Python; familiarity with bioinformatics workflows is a plus.

• Ability to translate complex biological questions into actionable experiments and scalable solutions.

• Experience writing study plans, SOPs, and detailed reports.

• Excellent organizational, communication, and time management skills.

• Demonstrated ability to lead projects and contribute strategically to a team-driven research environment.

• Up-to-date knowledge of developments in oncology and genomic technologies.

Locations:

• Europe: Paris / UK / Germany / Remote (EU)

About the role

We are looking for a scientifically credentialed strategist to lead the post-sales journey for our pharmaceutical partners. In this role, you will be the bridge between our cutting-edge foundational models and the R&D pipelines of the world’s leading biopharma companies.

You will use your deep expertise in machine learning and computational biology to build credibility with stakeholders, identify new opportunities for model application within their pipelines, and translate customer feedback into our product roadmap.

What you'll be doing

As our Applied AI Scientist (Pharma Partnerships) you are the primary architect of value for our most critical pharmaceutical partnerships. You will operate at the intersection of computational biology, ML and commercial scale across two strategic domains:

1. Partnership Value Realisation & Growth

• Post-Signature Leadership: Orchestrate the partner journey immediately following contract execution. You will act as the Project Manager for the deployment, ensuring seamless onboarding and integration of our foundational models.
• Scientific & technical thought-leadership: Consult with client R&D teams (ranging from bench scientists and data science teams to Heads of R&D) to diagnose their specific therapeutic challenges. Identify key use cases where our AI foundation models can unlock high value to our customers research and therapeutic priorities.
• Commercial Adoption & Growth: Proactively identify opportunities to expand the scope of the partnership. Leverage your understanding of the client’s pipeline to suggest new use cases, therapeutic areas, or departments where our technology can drive value.

2. Product Intelligence & Roadmap Influence

• Voice of the Customer: Synthesize technical feedback and performance metrics from the field. Translate complex biopharma user requirements into actionable technical specifications for our internal Research and Product teams. Identify high value opportunities to enrich our model capabilities and biology applications offering.
• Gap Analysis: Collaborate with our machine learning engineers to identify data modalities or functional gaps in our current offering, directly influencing future product iterations.

What you'll bring

The successful candidate will have a ‘team-first’ attitude; be independent, curious, and detail-oriented; thrive in a dynamic, fast-paced environment; and be fun to work with. We value individuals who bring deep domain expertise in computational biology, ML and pharmaceutical R&D alongside strong hands-on business development skills.

Scientific & Technical Credibility

• Educational Background: PhD in Computational Biology, Machine Learning, Bioinformatics, Genomics, or a related field is required.
• Domain Expertise: Deep understanding of the biopharma R&D value chain (target discovery to clinical trials). You understand the specific pain points of drug developers and are able to translate ambiguous biopharma use cases into rigorous ML applications.
• Technical Fluency:
• Deep experience in biological data modalities, notably multi-omics (single-cell, transcriptomics, proteomics) and histopathology slides.
• Extensive knowledge in modern ML architectures and paradigms like Transformers (ViT), GNNs, foundation models with embedding-based prediction heads (e.g., ABMIL), interpretability methods, and model evaluation & validation principles.
• Proven experience in designing end-to-end ML solutions for complex biological problems, including problem framing, data strategy and model design & evaluation
• Strong fluency in Python and deep learning frameworks (PyTorch, JAX)

Relationship & Strategic Skills

• Stakeholder Management: Proven experience navigating complex, matrixed organizations (Big Pharma experience is a plus). You can present to a VP of R&D in the morning and troubleshoot with a bioinformatician in the afternoon.
• Consulting Mindset: You are not just a support agent; you are a trusted advisor. You have experience in roles such as Field Application Scientist (FAS), Solution Architecture, or Scientific Consulting.
• Feedback Synthesis: Ability to distill complex client complaints or requests into clear, prioritized product requirements.

How to stand out:

• Experience in a startup or innovative environment, showing adaptability and proactiveness.
• A strong existing network within Global Top 20 Pharma R&D.
• Experience specifically with "Foundation Models" or Generative AI in a biological context.
• Track record of high-impact publications (Nature, Cell, NeurIPS).

The candidate journey

To be considered, please submit your CV in English.

We believe in a transparent and collaborative interview process. We need to find a fit for both you and the company. Here is what you can expect after submitting your application:

• Screening: Once you have applied, the hiring team will review your application. If your experience and skills align with the role, you will be invited to a 30-minute introductory call with the Hiring Manager to discuss your background, motivations, and the position in more detail.
• Interviews: Following a successful screening, you will be invited to a series of interviews:
  • Case Study (60 min): You will prepare a mock kick-off document for a client engagement with us to evaluate the model on their desired use-cases, including suggesting interesting use cases for our model and outlining the project plan. We want to see how well you understand the potential use cases for foundation models in the clinical stage of pharma development cycles, and how you would manage a key strategic partner through the deployment and delivery process.
  • Scientific Deep Dive Presentation (30 min): You will briefly present a piece of scientific work to a small panel of our researchers and engineers, led by a senior member of our technical team, and answer Q&S after (10-15 min presentation, 15-20 min Q&A). The content is up to you: it can be your own past research, a relevant paper in the field, or extra points if it’s a specific Bio-AI use case you’ve worked on with a biopharma. The goal is to assess your technical fluency, your ability to facilitate scientific debate, and how you communicate complex concepts to experts.
  • Executive Interview (30 min): A comprehensive discussion with member(s) of our Senior Leadership. This session moves beyond technical competency to focus on long-term vision, values, and mutual potential. This is an opportunity for you to get to know the company better as well.
• Offer: Following the completion of all interviews, our hiring team will make a final decision and will be in touch to share the outcome. Please note that an offer is contingent upon the successful completion of a reference check.
• Onboarding: We are happy to have you joining the team! Once you have accepted and signed your offer, we will be in touch to begin the process of onboarding you.

Why this is a unique opportunity

• A collaborative and mission-driven work environment.
• Competitive salary and equity package.
• Flexible work arrangements, including remote options.
• Opportunities for professional growth and leadership development.
• Shape the future of biology and AI by contributing to groundbreaking work.

The Team You’ll Join 

As part of Recursion's Value Tech Tooling Team, you will be at the forefront of reimagining drug discovery from first principles using our massive data capabilities. You'll work in a cross-functional team of world-class computational biologists and engineers who turn complex analyses and data workflows into stable tools and pipelines that multiply their impact and industrialise the discovery process across a wide array of therapeutic areas. You'll partner with biologists, medicinal chemists, engineers, data scientists, ML scientists, and to design experiments, develop new methods, build scalable data workflows, analyse results, and identify common themes across programs. As our toolbox grows and evolves, it will contribute to a revolution in drug discovery to bring life-changing therapeutics to patients at greater speed and with higher quality, safety and efficacy than ever before.

In this role, you will:

• Synthesize, integrate, and analyse diverse internal and external datasets from computational biology, target discovery, functional genomics, biomarker discovery, and real-world and clinically derived data sources, and identify commonalities to turn into reusable tools and pipelines.
• Build, maintain, and improve robust data pipelines and analytical workflows for complex biological datasets, including omics data, internally generated biological assay data, and external data sources such as Tempus and other real-world datasets.
• Develop and apply agentic workflows to integrate and orchestrate analyses across multiple internal and external data sources, accelerating insight generation and supporting scalable decision-making across drug discovery programs.
• Partner with engineers to mature pilot tooling and workflows into stable products and infrastructure that multiply the effectiveness of scientific collaborators pursuing drug programs.
• Present and discuss data, pipelines, and tools with decision makers and stakeholders in a clear and compelling way that drives toward getting medicines to patients.
• Collaborate cross-functionally with Recursion’s platform data science, data engineering, and ML teams to further advance Recursion’s ability to interpret and translate large-scale phenomics and multimodal data into therapeutic programs.

The Experience You’ll Need

• PhD in a relevant field (e.g., computational biology, bioinformatics, statistics, quantitative pharmacology, cancer/cell biology, computer science, or a related discipline), or equivalent experience, with a track record of applying these skills to fundamental problems in drug discovery.
• Experience applying computational methods (including statistical, probabilistic, and/or machine learning techniques) to analyse complex biological and/or human clinical data.
• Experience building, maintaining, and improving reproducible data pipelines and analytical workflows for large, heterogeneous biological datasets (Python strongly preferred).
• Experience working with high-dimensional biological datasets, including omics data (e.g., single-cell and other genomics-based modalities) and/or other complex assay modalities.
• Experience turning exploratory analyses into reusable tools, workflows, and documentation that can be adopted by other scientists/teams.
• General understanding of drug discovery and translational biology.

Nice To Have

• Experience working on highly collaborative cross-functional teams; ability to clearly explain computational analyses, data workflows, and methodologies to cross-functional and non-technical teams.
• Hands-on experience working with real-world clinical datasets (EHR/claims/registries) and/or generating real-world evidence (cohorting, endpoint definition, observational study considerations).
• Experience with real-world clinical datasets (e.g., EHR-derived oncology datasets) or demonstrated ability to rapidly learn new healthcare data modalities; experience with Tempus or similar datasets is a plus.
• Experience integrating multimodal datasets (e.g., genomics + phenomics, genomics + imaging) in service of translational decisions.
• Experience developing or applying agentic workflows to orchestrate analyses across multiple internal and external data sources, accelerating insight generation and decision-making

Working Location & Compensation:

This is an office-based, hybrid position at our office located in London, England. Employees are expected to work in the office at least 50% of the time.

At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is £86,300 - £115,500. You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. 

#LI-EP1

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.

Nilo Therapeutics is an early-stage biotech company developing groundbreaking therapies for autoimmune and inflammatory diseases. Our experienced team brings together diverse interdisciplinary expertise to modulate immune responses via activation of neural circuits. United by our passion for discovering and translating novel biology, we are dedicated to advancing human health through transformative science.  

We are backed by The Column Group, Lux, and DCVC Bio.   

Position 

We are seeking a highly motivated, on-site Investigator to join our Therapeutics Biology team. This role will be part of a team focused on foundational discovery biology, evaluating the therapeutic potential of our neuro-immune platform and validating targets at the bench across a broad range of autoimmune diseases.

Ideal candidates will use their scientific acumen and collaborative approach to partner across the interdisciplinary Nilo team on all aspects of the drug discovery process. This is an exciting opportunity to lead innovative research projects and make significant contributions to our mission of advancing therapeutic solutions. 

At Nilo Therapeutics, we are a dynamic start-up at the forefront of biotech innovation, driven to discover novel biology and develop new drugs. We seek team members who are inspired by our mission and thrive in a collaborative, rigorous, and entrepreneurial environment. Ideal candidates are self-motivated, proactive problem solvers, excited to build and grow the company alongside a world-class team. If you are comfortable with managing multiple projects and possess a resourceful, can-do attitude, we would love to hear from you. Join us and contribute to our mission of advancing innovative therapies at the intersection of neuroscience and immunology. 

What you’ll do: 

• Independently design and conduct both in vitro and in vivo models of inflammation
• Develop acute and chronic experiments in rodents to evaluate targets using inflammatory disease models 
• Utilize primary cell culture, multi-color flow cytometry, ELISA, basic molecular biology and immune assays to probe the neuro-immune axis
• Perform H&E / immunofluorescence staining and confocal microscopy
• Stay up to date with emerging scientific literature and contribute to the strategic vision of the company. 
• Collaborate cross-functionally with experts in Neuroscience, Bioinformatics, Drug Discovery and CROs to advance target identification and validation 
• Independently prepare data and present to the team 
• Work to improve existing animal protocols and implement solutions / troubleshoot as needed
  
  

Key Qualifications: 

• Ph.D. in Immunology, Biology, or a related discipline
• 5+ years of biotech or pharma industry experience for Principal Scientist, 8+ years for Investigator 
• Strong background in immunological assays, both in vitro, ex vivo, and in vivo
• Extensive hands-on experience working with disease models in rodents
• Hands-on experience with multi-color flow cytometry, confocal microscopy, primary cell culture, ELISA, and basic molecular biology techniques
• Excellent organizational and communication skills, with the ability to manage multiple projects and deadlines.
• Flexibility to learn new methods and skills for changing research priorities 
• Ability to keep detailed and organized records of experimental protocols and results 
• Ability to work independently and collaborate as member of a research team
• Ability to prioritize tasks, coordinate work tasks with others, and meet multiple deadlines 
• Proven ability to work collaboratively in a multidisciplinary team environment and motivated to make significant contributions for the growth of a high-paced start-up.
• A passion for high-quality, translational science and a desire to discover novel biology and new drugs

We offer a competitive compensation package that includes a range of benefits designed to support the well-being and professional growth of our team members. The base compensation range for this role is $160,000 - $210,000.

Nilo Therapeutics is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment. We are committed to creating a diverse and inclusive environment and encourage individuals from all backgrounds to apply. 

This is an exciting opportunity to independently lead Biostatistics efforts advancing Natera’s oncology portfolio of cutting-edge molecular diagnostic tests. As a Staff Biostatistician, you will leverage your strong applied statistics expertise to drive the strategy and execution of complex validation experiments for multiple high-priority projects. The ideal candidate will possess exceptional communication skills and a deep understanding of Biostatistics in analytical validation.

PRIMARY RESPONSIBILITIES:

• Strategic Study Design and Analysis: Independently lead the design, analysis, and interpretation of analytical validation studies for oncology products.

• Cross-Functional Leadership: Serve as the statistical lead on multiple high-priority project teams. Partner with bench scientists, bioinformatics, and product development teams to integrate statistical expertise into project planning and execution. Identify risks, communicate concerns, and champion solutions to interdisciplinary teams.

• Documentation and Reporting: Prepare comprehensive protocols and reports for cross-functional collaborators and stakeholders.

• Regulatory Compliance: Ensure statistical methodologies and analyses meet the standards set by regulatory agencies such as CAP/CLIA, NYS, and the FDA.

• Innovation and Improvement: Provide leadership on the application of both common and cutting-edge statistical methods for studies of varying complexity.

QUALIFICATIONS:

• Minimum 8 years of relevant industry experience, with a focus on analytical validation in diagnostics, biotechnology, or related industries.

• Ph.D. or Master's degree in Biostatistics, Statistics, or a related field.

KNOWLEDGE, SKILLS, AND ABILITIES:

• Expert-level knowledge of statistical methodology in diagnostic medicine, including a deep understanding of CLSI guidelines

• Exemplary written and verbal communication skills, with a specific talent for presenting to non-technical executive leadership

• Demonstrated ability and enthusiasm for working on cross-functional teams with members of diverse technical backgrounds

• Exceptional problem-solving skills and attention to detail

This is an exciting opportunity to independently lead Biostatistics efforts advancing Natera’s oncology portfolio of cutting-edge molecular diagnostic tests. As a Staff Biostatistician, you will leverage your strong applied statistics expertise to drive the strategy and execution of complex validation experiments for multiple high-priority projects. The ideal candidate will possess exceptional communication skills and a deep understanding of Biostatistics in analytical validation.

PRIMARY RESPONSIBILITIES:

• Strategic Study Design and Analysis: Independently lead the design, analysis, and interpretation of analytical validation studies for oncology products.

• Cross-Functional Leadership: Serve as the statistical lead on multiple high-priority project teams. Partner with bench scientists, bioinformatics, and product development teams to integrate statistical expertise into project planning and execution. Identify risks, communicate concerns, and champion solutions to interdisciplinary teams.

• Documentation and Reporting: Prepare comprehensive protocols and reports for cross-functional collaborators and stakeholders.

• Regulatory Compliance: Ensure statistical methodologies and analyses meet the standards set by regulatory agencies such as CAP/CLIA, NYS, and the FDA.

• Innovation and Improvement: Provide leadership on the application of both common and cutting-edge statistical methods for studies of varying complexity.

QUALIFICATIONS:

• Minimum 8 years of relevant industry experience, with a focus on analytical validation in diagnostics, biotechnology, or related industries.

• Ph.D. or Master's degree in Biostatistics, Statistics, or a related field.

KNOWLEDGE, SKILLS, AND ABILITIES:

• Expert-level knowledge of statistical methodology in diagnostic medicine, including a deep understanding of CLSI guidelines

• Exemplary written and verbal communication skills, with a specific talent for presenting to non-technical executive leadership

• Demonstrated ability and enthusiasm for working on cross-functional teams with members of diverse technical backgrounds

• Exceptional problem-solving skills and attention to detail

Role Summary

Prime Medicine is seeking an AI & Informatics Engineer to join our AI Foundry and support our pipeline delivery.  This includes designing and building the data and computational infrastructure that powers our prime editing programs. This role spans laboratory informatics, NGS pipeline development, and AI-enabled tooling, giving the right candidate a direct line from the work they do to the therapies we develop. You will partner closely with research scientists, computational biologists and technical development professionals, turning raw data into reliable scientific insights, and building automation and AI capabilities that let teams work faster and smarter.

Our ideal candidate brings strong software engineering fundamentals, hands-on NGS pipeline experience, a practical understanding of modern AI frameworks, and the biological intuition to translate scientific needs into working systems. Equally welcome are candidates who entered this space from the life sciences side and have built serious software skills along the way.

This is an action packed and dynamic role where the successful candidate will be involved in multiple programs and activities, so excellent organizational abilities, communications and strong collaboration are critical. The ideal candidate thrives when working in a fast-paced environment, working with purpose, and making an impact for patients.

Key Responsibilities

NGS Pipelines and Data Infrastructure

• Design, develop, and maintain scalable bioinformatics pipelines for NGS data analysis, including amplicon sequencing for on-target editing quantification, using Nextflow and Docker to ensure reproducibility.
• Build and maintain data infrastructure connecting NGS instruments, electronic laboratory notebooks (e.g., Benchling), data repositories, and AWS cloud compute, including automated data ingestion, scalable storage, and provenance tracking.
• Build APIs, MCPs, dashboards, and other internal tools that expose genomic data and analytical capabilities to scientific and cross-functional teams.

Laboratory Informatics

• Support implementation and ongoing development of laboratory informatics systems, including data ingestion from key instruments and integration with laboratory data platforms such as Benchling.
• Support vendor relationships and delivery outcomes for external collaborators, driving requirements, managing implementations, and ensuring high-quality delivery.

AI-Powered Tools and Automation

• Build AI-powered and agentic capabilities that automate routine work, support scientific reasoning, and improve how data and knowledge flow across the organization.
• Develop reusable platform components for retrieval, orchestration, and model interaction, with human-in-the-loop workflows that make AI systems transparent and practical for scientific users.
• Identify and address automation opportunities and scalability bottlenecks across research and operational workflows.

Engineering Practices

• Write production-grade code using Git-based workflows, peer review, testing, CI/CD, and documentation best practices; convert research prototypes into robust, maintainable software.
• Build integrations between internal tooling and third-party platforms to support evolving scientific and operational needs.
• Participate in cross-functional projects spanning lab operations, software engineering, and bioinformatics; recommend best practices, system architectures, and design patterns.
• Perform code reviews and contribute to documentation of engineering and cross-functional practices.

Qualifications

Required

• BS with 5+ years or MS with 3+ years of industry experience in Engineering, Bioinformatics, Data Sciences, or a related field. Candidates with biotech or life sciences with substantial software experience are strongly preferred.
• Strong Python development; proficiency with Nextflow (or comparable workflow tools), Docker, AWS, Linux/Unix, and Git.
• Experience developing and deploying bioinformatic data infrastructure, particularly NGS analysis pipelines.
• Experience implementing or integrating laboratory informatics systems, preferably including Benchling.
• Experience developing and maintaining production-grade APIs and SDKs, and rolling out software tooling across an organization.
• Familiarity with LLM frameworks and practical judgment about where agentic approaches add genuine value.
• Track record of shipping software that scientific or technical users adopt and rely on.

Preferred

• Experience building and deploying AI-powered tools or agentic systems in production or research settings.
• Familiarity with gene editing applications (CRISPR, base editing, or prime editing), including amplicon-seq workflows and tools such as CRISPResso.
• Familiarity with relational databases and data visualization tools (e.g., Plotly Dash, Streamlit, Spotfire).
• Experience in a GxP or regulated software environment (21 CFR Part 11, GAMP 5).
• Experience owning vendor relationships and delivery outcomes for external collaborators in laboratory informatics contexts.

Why This Role

Prime editing is a precise technology, and that precision depends on strong informatics, software, and scientific infrastructure. If you believe that better systems, better automation, and better access to data can translate into safer and more effective therapies, this is the right environment. You will build tools that directly shape how Prime generates, analyzes, and acts on scientific data, while helping lay the foundation for programs to come.

The Opportunity:

We are seeking a Senior People Operations & Compliance Specialist to support and scale our People function in the United States. This role will play a critical part in ensuring that our HR operations run smoothly while maintaining full compliance with U.S. employment laws and internal policies.

The ideal candidate is a highly organized, detail-oriented HR professional with experience managing the employee lifecycle, HR compliance, benefits administration, and HR systems in a fast-paced, growing environment. Experience in biotech, healthcare, or other regulated industries is a must.

This role will partner closely with leadership, finance, and employees to ensure a seamless employee experience while maintaining strong operational rigor and compliance standards.

How you’ll contribute:

Employee Lifecycle

• Oversee end-to-end employee lifecycle processes, including onboarding, transitions, and offboarding.

HR Compliance

• Ensure compliance with U.S. federal, state, and local employment laws, including wage and hour regulations, employee classification, and leave policies.
• Manage I-9 verification and employment eligibility compliance, including coordination with E-Verify where applicable.
• Maintain HR compliance documentation and support internal or external audits as needed.
• Partner with our external labor advisor when necessary to ensure compliance with evolving employment regulations.
• Support workplace investigations and policy enforcement processes when required.

Benefits Administration

• Administer, manage, and propose improvements on the employee benefits programs, including health insurance, retirement plans (401k), and other employee benefits offerings.
• Coordinate benefits enrollment processes, including new hire enrollments and annual open enrollment.
• Serve as liaison between employees and benefits providers to resolve issues and answer questions.

HR Systems & Data Management

• Maintain and ensure data integrity within the company’s HRIS system.
• Manage employee data updates, reporting, and HR documentation within HR systems.
• Support HR reporting and provide data insights related to workforce metrics when needed.

Payroll Coordination

• Coordinate with Finance and payroll providers to ensure accurate processing of payroll inputs, including new hires, compensation changes, bonuses, and terminations.
• Review payroll data for accuracy and resolve discrepancies as needed.

HR Programs & Process Improvement

• Support the implementation and administration of HR programs such as performance reviews, employee engagement initiatives, and internal HR policies.
• Identify opportunities to improve HR processes, systems, and employee experience.
• Contribute to the development and maintenance of HR policies and the employee handbook.

Business partner

• Works closely with the Operations department to align HR initiatives with business goals.

Qualifications

• 7+ years of experience in HR operations, people operations, or HR compliance roles.
• Strong knowledge of U.S. employment laws and HR compliance requirements.
• Experience managing benefits administration and employee lifecycle processes.
• Experience working with HRIS platforms (e.g., BambooHR, Rippling, ADP, Workday, or similar).
• Strong organizational skills and exceptional attention to detail.
• Ability to manage sensitive and confidential information with professionalism and discretion.
• Strong communication and problem-solving skills.
• Ability to work independently in a fast-paced and evolving environment.

Preferred Qualifications

• Experience in biotech, healthcare, life sciences, or other regulated industries.
• Experience supporting a fast-growing company or startup environment.
• Familiarity with multi-state employment compliance in the U.S.
• HR certification such as SHRM-CP, SHRM-SCP, or PHR is a plus.

What we´ll offer:

• 22 days of PTO with the possibility to carry over 10 days to the following year.
• Company Holidays, plus your Birthday off! 
• Company-sponsored benefit plans, including medical, dental, and vision insurance plus life, STD, and LTD coverage, and 401(k).
• Flexible work schedule 
• And more to come!

We’re looking for a Staff Quantum Applications Scientist - Life Sciences who will be part of a cross-functional team at IonQ whose mission is to deliver the world’s best quantum solutions in life sciences on the world’s best quantum computers to solve the world’s most complex and impactful problems. This role is open as part of IonQ’s Quantum Applications team based in either Gothenburg, Sweden or Toronto, Canada. You will work closely with partners within the life sciences innovation ecosystem and beyond to create new hybrid quantum applications with significant commercial impact.

Responsibilities: 

• Originate and lead development of impactful hybrid quantum applications, algorithms and solutions in the life sciences domain that promise commercial advantages in practice and at scale.
• Collaborate with quantum compiler, cloud and hardware engineering teams to develop highly optimized hybrid workflows for trapped-ion quantum computers.
• Contribute knowledge of classical and quantum domain-specific algorithms and tools to evaluate and communicate pros and cons, current state-of-the-art, scaling behavior, trade offs, cross-over points, etc.
• Lead constructive technical interactions with client teams to find, define, and solve problems of real-world interest using IonQ trapped-ion quantum computers.
• Represent the team in client and stakeholder presentations, develop presentation content and appropriately adapt it to the audience.
• Build reusable software platforms to grow IonQ’s user base. Integrate first of a kind quantum algorithms into larger end-to-end workflows.

You’d be a good fit with: 

• Doctorate degree in the life sciences domain, or equivalent work experience.
• At least 3 years of professional experience using and developing computational and ML/AI tools in bioinformatics, molecular biology, development of advanced therapeutics, including a track record of peer-reviewed manuscripts and contributions to code bases.
• At least 3 years of professional experience developing, applying, validating quantum computing algorithms and solutions in the life sciences domain, including prototyping solutions using Python and quantum SDKs like Qiskit, PennyLane, Cirq.
• Desire to work closely with customers including aligning with time zones and work schedules. Potential for international travel and/or onsite co-location.

You’d be a great fit with:

• Expertise in key mathematical techniques used in quantum computing - linear algebra, matrix decompositions, probability theory, symmetry, computational complexity.
• Success working directly with clients to define and deliver solutions; excellent collaboration and communication skills.

Location: Onsite and/or hybrid from our office in Gothenburg, Sweden or Toronto, Canada
Travel: 10% domestic and international, with a focus on visiting customers and clients
Job ID: 1361

We’re looking for a Senior Quantum Applications Scientist - Life Sciences who will be part of a cross-functional team at IonQ whose mission is to deliver the world’s best quantum solutions in life sciences on the world’s best quantum computers to solve the world’s most complex and impactful problems. This role is open as part of IonQ’s Quantum Applications team based in either Gothenburg, Sweden or Toronto, Canada. You will work closely with partners within the life sciences innovation ecosystem and beyond to create new hybrid quantum applications with significant commercial impact.

Responsibilities: 

• Develop impactful hybrid quantum applications, algorithms and solutions in the life sciences domain that promise commercial advantages in practice and at scale.
• Collaborate with quantum compiler, cloud and hardware engineering teams to develop highly optimized hybrid workflows for trapped-ion quantum computers.
• Contribute knowledge of classical and quantum domain-specific algorithms and tools to evaluate and communicate pros and cons, current state-of-the-art, scaling behavior, trade offs, cross-over points, etc.
• Be part of a client-facing team that finds, defines, and solves problems of real-world interest using IonQ trapped-ion quantum computers.
• Build reusable software platforms to grow IonQ’s user base. Integrate first of a kind quantum algorithms into larger end-to-end workflows.

You’d be a good fit with: 

• Doctorate degree in the life sciences domain, or equivalent work experience.
• Hands-on expertise with using and developing computational and ML/AI tools in bioinformatics, molecular biology, development of advanced therapeutics, including a track record of peer-reviewed manuscripts and contributions to code bases.
• Demonstrated experience developing, applying, validating quantum computing algorithms and solutions in the life sciences domain, including prototyping solutions using Python and quantum SDKs like Qiskit, PennyLane, Cirq.
• Desire to work closely with customers including aligning with time zones and work schedules. Potential for international travel and/or onsite co-location.

You’d be a great fit with:

• Expertise in key mathematical techniques used in quantum computing - linear algebra, matrix decompositions, probability theory, symmetry, computational complexity.
• Success working directly with clients to define and deliver solutions; excellent collaboration and communication skills.

Location: Onsite and/or hybrid from our office in Gothenburg, Sweden or Toronto, Canada
Travel: 10% domestic and international, with a focus on visiting customers and clients
Job ID: 1360

Your Impact at LILA

Cloud Security & Compliance Lead is responsible for the end-to-end security, governance, risk management, and regulatory compliance of Lila Sciences’ cloud environments and research workflows. You’ll own cloud security architecture, policy frameworks, data protection, and compliance programs across multi-cloud and on-premises contexts as appropriate. You’ll partner with Engineering, Data Science, IT, Legal, and Compliance to codify secure patterns, enable rapid yet safe experimentation, and maintain a robust governance program with auditable evidence for regulators and customers.

What You'll Be Building

Cloud Security Architecture & Governance

• Define and maintain cloud security strategy, reference architectures, and security baselines for public cloud (AWS, Azure, GCP) and hybrid deployments. 
• Implement secure-by-default patterns for CI/CD is intentionally out of scope; focus on secure design patterns for cloud resources, data flows, and analytics. 
• Establish IAM least privilege, network segmentation, private endpoints, key/secret management, and centralized logging across AWS, Kubernetes (where applicable), and cloud-native services. 

Governance, Compliance & Risk Management

• Develop, implement, and continuously improve policies, standards, and procedures aligned to applicable frameworks (e.g., NIST CSF, NIST 800-53, FedRamp, ISO 27001, SOC 2, GDPR/CCPA). 
• Lead data protection program: data classification, data minimization, data retention, and data lifecycle management; oversee DLP strategies where relevant. 
• Manage third-party risk assessments, vendor security questionnaires, and contract security annexes; maintain evidence for audits. 

Security Controls & Monitoring

• Define and oversee security controls across cloud resources, including identity, access management, encryption, key management, log collection, and telemetry. 
• Collaborate with Security Operations to establish monitoring, alerting, incident response coordination, and evidence collection for audits. 

Compliance & Audit Readiness

• Prepare for internal and external audits; map controls to frameworks and translate them into engineering artifacts and evidence. 
• Maintain alignment with SOC 2, ISO 27001, and other regulatory requirements, coordinate with Legal and Privacy on data protection controls. 

Data, ML/AI Security & Privacy

• Ensure secure data movement, storage, and access patterns; implement data lineage and isolation for training vs. inference in ML workflows. 
• Address privacy-by-design considerations in data science processes; oversee secure handling of sensitive datasets. • Collaboration & Enablement 
• Partner with Engineering, IT, Legal, and Commercial teams to ensure cohesive risk management. 
• Provide security training and awareness for engineering, data science, and product teams; translate security requirements into actionable tasks. 

Evidence & Documentation

• Create and maintain security documentation, runbooks, policies, and evidence packs suitable for audits and regulator requests.

What You’ll Need to Succeed

• Education: Bachelor’s degree in computer science, Information Security, Cybersecurity, Engineering, or related field. Masters preferred.
• Experience: 5–8+ years in cloud security, information security, or a related role; hands-on experience with cloud environments (AWS, Azure, GCP) and Kubernetes is a plus; experience in governance, risk, and compliance activities.
• Certifications: CISSP, CISM, CCSK, ISO 27001 Lead Auditor, SOC 2 Practitioner, or cloud security certifications are desirable.
• Technical Skills:  Strong understanding of cloud architectures, IAM, encryption, KMS, secret management, data protection, and network security.
• Familiarity with Kubernetes concepts and security considerations (RBAC, network policies, pod security standards) as they apply to governance and compliance contexts. 
• Experience with policy frameworks and policy-as-code concepts (OPA, Kyverno, Checkov) for governance and automated compliance checks.
• Knowledge of SBOMs, software supply chain concepts, artifact signing (Cosign/Sigstore), and SBOM generation. 
• Familiarity with audit-ready control mapping, risk assessment, and remediation tracking.
• Soft Skills: Excellent communication, stakeholder management, and the ability to translate complex security requirements into actionable business and engineering tasks.

Bonus Points For

• Experience with data-intensive research environments, HPC, or bioinformatics workloads.
• Familiarity with privacy by design, data governance, and model governance in ML/AI contexts.
• Prior startup or high-growth experience enabling developer velocity with strong guardrails; knowledge of Sigstore/Cosign and SLSA concepts for software supply chain integrity.
• Experience with at least one modern programming language (Python, Go, Rust, JavaScript) for automation or tooling.

Your Impact at LILA

We are seeking a strategic Product Marketing Manager (Life Science) to own go-to-market for Lila’s life science product portfolio. You’ll translate complex, closed-loop AI and lab capabilities—such as mRNA design, DNA construct optimization, and AI-driven medicinal chemistry—into clear, credible stories and compelling commercial offerings for:

• Biopharma and advanced therapy companies
• R&D and CMC leaders
• Data science / AI teams and scientific IT

In collaboration with the Life Science Product team, you will shape RNA and DNA design technology tiles, hit-to-lead and lead optimization offerings, and early commercial pilots. Your work will define positioning, launch plans, and evidence strategies that move prospects from curiosity to committed programs. You’ll articulate value, build differentiated narratives, and enable cross-functional execution across product, sales, and customer success to accelerate adoption and drive measurable business impact.

What You'll Be Building

Messaging & Positioning

• Define and continuously refine product narratives for Lila’s life science capabilities (RNA/mRNA design, DNA constructs, protein and small molecule optimization, AISF-powered workflows).
• Tailor messaging to specific personas (Heads of R&D, Therapeutic Area leaders, CMC, translational and bioinformatics leads, Scientific IT) and use cases (hit-to-lead, mRNA design, in vivo CAR-T data stories).
• Ensure all external materials reflect Lila’s master narrative on scientific superintelligence, safety, and multi-domain learning.

Go-To-Market Strategy & Launch

• Lead end-to-end GTM for new life science capabilities: from beta/pilot framing through general availability and expansion.
• Partner with Product, Commercial, and BizOps to define offer constructs (pilot scopes, pricing guardrails, AISF access models) and map the customer journey from first meeting to signed programs.
• Align roadmap milestones (new RNA/DNA or medicinal chemistry capabilities, app workflows) with external launch moments, events, PR, and sales cycles.

Content & Evidence Creation

• Produce technical and visionary content that makes capabilities tangible:
  • Use case briefs, technical one-pagers, solution guides
  • Decks for customer pitches, partner discussions, and scientific meetings
  • Blog posts, webinar scripts, demo narratives, and explainer videos in partnership with Brand/Creative
• Collaborate with Life Science (LS) Product, science, and commercial teams to turn pilots and tech tiles into case studies showing real impact

What You’ll Need to Succeed

Education

• Bachelor’s degree in Life Sciences, Bioengineering, Data Science, or a related field. MS/PhD a plus.

Experience

• 5+ years in Product Marketing or closely related roles at a B2B SaaS, life sciences technology, or AI/ML company, ideally supporting discovery, translational, or CMC/R&D teams.

Domain Expertise

• Working knowledge of the life science value chain (discovery → preclinical → early development; RNA/DNA/protein or small molecule workflows).
• Familiarity with lab automation, assay platforms, FAIR data principles, and AI/ML in drug discovery or therapeutics.

Technical Fluency

• Comfortable engaging with AI scientists, bench scientists, and engineering/IT stakeholders; able to translate closed-loop AI and AISF concepts into clear business value.

Communication & Storytelling

• Exceptional writing and presentation skills, with a track record of content targeting scientific and technical audiences.

Cross-Functional Collaboration

• Proven success partnering across Product, Sales/BD, and Marketing; able to influence without formal authority.

Startup Mindset

• Thrives in a fast-moving, highly cross-functional environment where both the product and category are evolving.

Bonus Points For

• PHD is a plus

Position Summary

Alamar Biosciences is seeking a Senior Scientist, Technology Development to innovate technologies and products based on our proprietary NULISA™ platform, which enables highly sensitive, quantitative, and multiplexed biomarker measurements using qPCR and/or NGS readouts. The ideal candidate will have a strong background in assay development, immunoassays, molecular biology, biochemistry, and data analysis, along with a passion for translating novel technologies into robust products. This role will involve close collaboration with product development, bioinformatics, manufacturing, and software teams. The fast-paced nature of this position requires excellent attention to detail, strong communication skills, the ability to multitask and work independently, and flexibility with evolving priorities and schedules. This is a full-time, onsite role based in Fremont.

Duties and Responsibilities

• Lead development of novel multiplex immunoassays utilizing Alamar’s proprietary NULISA technology
• Design, execute, and troubleshoot experiments to optimize assay performance
• Perform rigorous data analysis and interpretation to guide technology and assay development decisions
• Identify key variables impacting assay sensitivity, specificity, robustness, and reproducibility, and drive systematic optimization
• Participate and present data in technical discussions and project meetings.
• Collaborate closely with bioinformatics, product development, manufacturing, engineering, and software teams to enable end-to-end workflow integration
• Support assay transfer, automation, and system-level integration onto Alamar’s proprietary instrument platform
• Mentor and provide technical guidance to junior scientists and contribute to team-level scientific excellence
• Contribute to building and maintaining a strong, collaborative team culture

Qualifications

• PhD with 5+ years of experience in Molecular Biology, Biochemistry or a related field
• Demonstrated experience in single-plex and multiplex immunoassay development
• Hands-on experience with reagent optimization for immunoassays and qPCR/NGS
• Experience with qPCR /NGS assay optimization
• Ability to maintain cooperative working relationships with a broad range of stakeholders, including team members and cross functional teams
• Strong organizational skills with the ability to set priorities and balance laboratory and cross-functional needs
• Highly detail-oriented with a strong focus on quality
• Consistent, positive, and can-do attitude

Preferred Qualifications

• Preferably PhD with 5+ years of industry experience, MS with 8+ years of industry experience or BS with 10+ years of industry experience.
• Experience with immunoassay technologies such as NULISA, SIMOA, PEA, or similar technologies
• Experience with optimizing multi-color qPCR or NGS assays
• Experience with calibration curve–based sample quantification
• Prior experience leading or managing direct reports, including mentoring junior scientists or associates
• Familiarity with data and record management platforms such as Benchling or SciNote
• Experience with reagent and inventory management
• Excellent written and verbal communication skills, with the ability to present technical information to diverse audiences

The base salary range for this full-time position is $140,000 - $165,000 + bonus + equity + benefits. Our salary ranges are determined by work location, job-related skills, experience, and relevant education or training. The ranges displayed on each job posting reflect the minimum and maximum target for new hire salaries but are subject to change if the leveling of the role is adjusted. Your recruiter can share more about the specific salary range during the hiring process. 

Position Summary

We are seeking a highly motivated Scientist I to join the Content Development team. In this role, you will support the development, optimization, and characterization of NULISA-based immunoassays and multiplex proteomic panels across diverse disease areas. You will work closely with cross-functional partners including R&D, Manufacturing, Bioinformatics, and related teams to ensure robust assay performance and high-quality deliverables.

The ideal candidate will bring strong hands-on immunoassay execution skills, a solid foundation in data analysis, and the ability to contribute effectively in a fast-paced, collaborative product development environment.

Duties and Responsibilities

• Design, development, and optimization of multiplex proteomic panels across various disease areas to support biomarker discovery, validation, and translational research.
• Develop and optimize the high-plex panels to ensure high specificity, sensitivity, and reproducibility of the product.
• Perform multivariate analysis to optimize assay performance, minimize cross-reactivity and mitigate matrix effect.
• Troubleshoot technical challenges via root-cause analysis and implement corrective strategies.
• Develop and maintain critical documentation, including SOPs, PRDs, and assay transfer documents to support product development and regulatory compliance.
• Collaborate cross-functionally to advance projects and contribute to strategic discussions.

Qualifications

• Ph.D. in Biochemistry, Molecular Biology, or a related discipline with 0–3 years of relevant industry experience; M.S. with 2–5 years of experience will also be considered.
• Hands-on experience with immunoassays or multiplex assay platforms (e.g., Luminex, MSD, Olink, Ella, SomaLogic, etc.).
• Familiarity with molecular biology methods (e.g., qPCR, ddPCR, or NGS) is a plus.
• Strong problem-solving and analytical skills with attention to detail in experimental execution.
• Ability to manage time effectively, work collaboratively, and adapt in a fast-paced environment.
• Strong communication skills, including data presentation and technical documentation.
• Knowledge of biomarker research, assay validation, or clinical sample testing is desirable.

The base salary range for this full-time position is $120,000 - $140,000 + bonus + equity + benefits. Our salary ranges are determined by work location, job-related skills, experience, and relevant education or training. The ranges displayed on each job posting reflect the minimum and maximum target for new hire salaries but are subject to change if the leveling of the role is adjusted. Your recruiter can share more about the specific salary range during the hiring process. 

About The Role

10x Genomics is establishing a diagnostics effort, translating our leading single-cell and spatial assay technologies into impactful clinical applications. We are seeking a Scientist II to join the clinical bioinformatics team. The ideal candidate excels at distilling complex biological questions into actionable computational strategies, implementing computational/statistical methods and applying them to large-scale single-cell or spatial transcriptomics datasets to derive clinically meaningful insights.

The role requires a biology-first mindset, proficiency with large-scale bioinformatics analyses, strong scientific acumen and statistical rigor. The successful candidate will have an opportunity to work with some of the largest biomedical datasets assayed using cutting-edge 10x Genomics technologies, deriving clinical insights that power the next generation of clinical diagnostics.

What You Will Be Doing:

• Implement rigorous computational/statistical methods for single-cell and spatial transcriptomics data analysis.
• Derive actionable insights from clinical/translational single-cell or in-situ spatial datasets.
• Design, implement and validate biomarkers for diagnostic applications.
• Implement and maintain bioinformatics pipelines for reproducible, large-scale data processing.
• Process and analyze single-cell or in-situ spatial transcriptomics datasets spanning hundreds to thousands of samples.

To Be Successful, You Will Need:

• Ph.D. in bioinformatics, computational biology, genomics or a related discipline with extensive hands-on experience in single-cell NGS data analysis.
• A minimum of 2 years of industry experience post Ph.D.
• Experience analyzing large-scale single-cell or spatial transcriptomics datasets to derive biologically meaningful insights and/or diagnostic biomarkers.
• In-depth understanding of the assumptions, limitations and caveats of statistical methods.
• Experience developing and optimizing high-performance, scalable code.
• Proficiency working in a Linux environment.
• Goal-oriented, self-motivated and an independent problem solver.
• Meticulous attention to detail and a conscientious work ethic.

Preferred Skills

• Hands-on experience with 10x Genomics single-cell and in-situ transcriptomics technologies is a strong preference
• Hands-on research experience in cancer or autoimmune diseases is a strong preference
• Knowledge of clinical genomics, biomarker discovery and diagnostics
• Development of statistical models and algorithms for single-cell or spatial transcriptomics data
• Application of machine learning, particularly in the context of genomics
• Proficiency with workflow orchestration frameworks such as Snakemake, Nextflow or Martian
• Programming best practices including data analysis reproducibility, version control, design patterns, testing, debugging and profiling
• Track record of writing production-level code or maintaining published software packages
• High-throughput computing infrastructure such as HPCs or cloud computing

Location: United States (Willingness to travel to Japan 1-2x a year - Japanese fluency in language and culture is a requirement)

Company Overview: Natera, Inc. is a clinical genetic testing company based in Austin, Texas that specializes in non-invasive, cell-free DNA (cfDNA) testing technology, with a focus on women’s health, cancer, and organ health. Natera’s proprietary technology combines novel molecular biology techniques with a suite of bioinformatics software that allows detection down to a single molecule in a tube of blood. Natera operates CAP-accredited laboratories certified under the Clinical Laboratory Improvement Amendments (CLIA) in San Carlos, California, and Austin, Texas.

Position Summary: The mission of the Oncology User Experience Product team is to ensure that our customers and patients receive best-in-class experiences that resolve frictions to better patient care. The Senior Product Manager for Oncology Provider Solutions, Japan, will own the scale of our key product lines in the Japanese market and will join a growing team that shares the critical role of being the voice of our many internal and external users. Additionally, you’ll have the chance to make meaningful contributions to the broader Oncology portfolio, supporting initiatives for products in the primary US business as well.

You will work closely with business development, regulatory, engineering, design, and operations to create a vision, strategy, and thorough plan to scale our Provider Portal and drive growth in our clinical workflows. You will be acting as a full-stack PM, leading a cross-functional team in conducting user interviews, uncovering user pain points, gathering requirements, writing BRD/PRDs, creating user stories, defining acceptance criteria, and leading the scale of our Provider Portal for Japan. You will play a central role in developing country-wide user experiences that will reach millions of patients and their families.

About You: You care about improving outcomes for patients and clinicians and want your work to have real impact. You're comfortable navigating ambiguity, working across teams, and making decisions with imperfect information. You give and receive candid feedback, take ownership of hard problems, and don't wait to be told what to do. You possess Japanese fluency in language, culture, and regulation, and are excited by the opportunity to grow our business in Japan where there is enormous market potential and help drive a paradigm shift in how oncology care is delivered.

If you enjoy moving quickly, accomplishing aspirational goals in an ever-changing environment, and launching truly impactful products, this role is for you.

Primary Responsibilities

• Develop a deep understanding and appreciation of our users, including customers, patients, business partners, the commercial team, and customer operations, as well as their workflows, behaviors, and environments
• Partner with various stakeholders such as commercial product team, regulatory affairs, customer operations, and the local Japanese business team to gather insights and align on priorities
• Collaborate with our full suite of UX product development teams to translate business and market needs into clear, well-scoped requirements for the Japanese market
• Maintain a vision of industry trends and competitive landscape to ensure you know what makes a best-in-class user experience for your product line
• Develop well-thought, user-centric strategies and roadmap for your products
• Own product development lifecycle from design to deployment
• Define what success looks like for your product, measure it, and drive improvements
• Communicate with senior-level stakeholders to champion your roadmap and gain buy-in
• Help define and enhance the culture of the Oncology UXPM team, our Product org, and Natera at large

Qualifications

• Japanese fluency in language and culture
• Understands and able to exhibit Japanese business acumen
• Empathetic, user-centric thinker with exceptional integrity
• 3-5+ years of experience in software product management, ideally in the digital health, healthcare, or biotech industry
• Experience with regulated products and regulatory affairs in the US and/or abroad
• Extensive experience in conceptualizing, defining, and creating high-quality customer experiences
• Experience building solutions from start to finish
• Excellent communication, facilitation, presentation, relationship-building, and analytical skills
• A successful track record of cross-functional leadership
• Well-developed systems thinking and problem-solving frameworks
• Desire to roll sleeves up and get projects across the finish line
• Willingness to travel to Japan 1-2x per calendar year

About this opportunity:

At Freenome, we are seeking a Director, Technical Product Management to help grow the Freenome Product Management team. The ideal candidate is a seasoned leader who bridges the gap between complex molecular biology and scalable software products in a regulated environment. This person is responsible for the technical roadmaps, feature prioritization, software requirements, and specification definition related to Lab Information Management Systems (LIMS), laboratory automation, and software managing sample processing-to-result generation. You are passionate about building seamless, high-throughput clinical workflows that ensure data integrity and regulatory compliance, and you will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer. 

The role reports to the Director, Product Management. This role will be a Hybrid (based in our Brisbane, California headquarters) or Remote role. 

What you’ll do:

• Define and execute the multi-year technical roadmap for IVD/LDT software platforms, ensuring alignment with clinical needs and regulatory requirements.
• Lead feature prioritization and software requirements definition of LIMS, lab automation, and software managing the sample processing-to-result generation to optimize high-throughput sample processing and data integrity.
• Direct the integration of complex diagnostic hardware with cloud-based or on-premise processing software, focusing on seamless end-to-end workflows.
• Ensure all software products comply with global regulatory standards, including FDA, CLIA/CAP, ISO 13485, and HIPAA/GDPR data privacy requirements.
• Collaborate with R&D, Molecular Biology, Clinical Lab, Lab Automation, and Engineering teams to translate complex assay protocols into automated, scalable software requirements.
• Ensure compliance to Software Development Life Cycle (SDLC) for diagnostic products, from initial concept to commercial launch for deliverables owned by Technical Product Management.
• Manage cross-functional dependencies between wet-lab operations, bioinformatics pipelines, and software engineering teams to ensure timely product delivery.
• Establish and monitor key performance indicators (KPIs) for software reliability, processing speed, and diagnostic accuracy in a clinical laboratory environment. 

Must haves:

• 8+ years in Technical Product Management, with at least 4 years specifically in IVD, Medical Devices, or Clinical SaaS.
• Proven experience with LIMS/LIS and laboratory automation workflows.
• Deep familiarity with FDA software guidelines and CLIA regulations.
• BS/MS in Computer Science, Bioengineering, Molecular Biology, or a related field.
• Demonstrated experience managing and scaling technical product teams in a regulated environment.
  

Nice to haves:

• MS or PhD in a technical or scientific field.
• Experience with Next-Generation Sequencing (NGS) data pipelines.
• Hands-on experience with cloud infrastructure (AWS/Azure/GCP) in a GxP environment.

Benefits and additional information:

The US target range of our base salary for new hires is $220,400 - $281,400. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-REMOTE

The Team

Our AI research team sits at the heart of our mission to unlock new dimensions of biological understanding. You will leverage state-of-the-art AI to accelerate discovery and drive transformative insights in biology—developing novel AI models purpose-built for biological research, engineering robust systems that enable breakthrough science at unprecedented scale, and translating these advances into practical tools that empower researchers worldwide.

Our approach is comprehensive and integrated, bringing together world-class AI model development, exceptional engineering talent, high-quality biological data, powerful computing infrastructure, and strategic partnerships. Success requires excellence across five interconnected pillars: training frontier AI models specifically for biology; building engineering systems that maximize research velocity and efficiency; executing a sophisticated data strategy that fuels AI development; operating a world-class AI compute platform; and creating impactful products that transform AI capabilities into accessible scientific tools.

The Opportunity

This role is part of the Data team, which focuses on owning the strategy, sourcing and implementation for data supporting AI research and development. Our goal is to maximize the speed, agility, and capability of biological AI research by connecting public data resources and Biohub's experimental platforms to AI systems.

The data that trains biological frontier models comes in dozens of modalities—sequences, images, spatial coordinates, time series, molecular structures, metadata, preprints and published papers—each with its own noise characteristics, biases, and information content. The question of how to represent this data for learning is one of the most important open problems in biological AI.

You will operate with broad scope and high autonomy, influencing roadmap decisions across teams while mentoring senior individual contributors. Success in this role means scaling data systems that are not only large, but adaptive, interpretable, and scientifically grounded, accelerating progress toward robust biological frontier models and ultimately advancing human health.

We're looking for data scientists who can work at this frontier: people who understand biological measurement deeply, think creatively about data representations and tokenization strategies, and can translate that thinking into novel training architectures. You'll work directly with experimental and computational scientists, data scientists and  AI researchers to define what the models see and how they see it, and data engineers to make this work at scale. This is a role for someone who wants to invent the methods that make biological frontier models possible.

What You'll Do

• Design data representations and tokenization strategies for imaging data that enable novel model architectures

• Coordinate Experimental, Data Science, Data Engineering and AI Research teams to translate biological structure into learnable representations—defining priorities and appropriate structures for metadata and data that information models can access and consume

• Work across those teams to guide data acquisition priorities, define quality criteria, and assess external datasets from a representation perspective

• Develop and validate approaches for combining heterogeneous data modalities into unified training frameworks, designing for robustness to noise, bias, and batch effects

• Evaluate how representation choices impact model performance, identifying which biological signals are captured or lost and iterating to improve

What You'll Bring

• PhD in computational biology, bioinformatics, or a quantitative biological field
• Experience with tokenization strategies for non-text data (images, sequences, graphs, time series)
• Track record of novel methodological contributions (publications, open-source tools, or production systems)
• Familiarity with biological foundation models (ESM, scGPT, or similar)
• Deep understanding of imaging data, their underlying data characteristics, and how to transform raw data into ai-ready datasets.
• Experience designing data representations or feature engineering for machine learning, ideally in scientific or biological contexts
• Familiarity with modern ML architectures (transformers, diffusion models, or similar) and how data representation choices affect learning
• Strong computational skills (Python, scientific computing libraries); comfort working with large-scale datasets
• Creative, first-principles thinking about how to structure data for learning

Compensation

The Redwood City, CA  base pay range for a new hire in this role is $214,000 - $294,800. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

This position may be eligible to participate in Biohub's discretionary annual performance bonus program. Bonus eligibility and targets are determined in accordance with Biohub's total rewards philosophy and may vary by role.

Better Together

As we grow, we’re excited to strengthen in-person connections and cultivate a collaborative, team-oriented environment. This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in-office days determined by the team’s manager. The exact schedule will be at the hiring manager's discretion and communicated during the interview process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

If you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.

#LI-Hybrid 

The Team

The Biohub in New York is an independent nonprofit research institute that brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine. Biohub itself supports some of the brightest, boldest engineers, data scientists, and biomedical researchers to investigate the fundamental mechanisms underlying disease and develop new technologies that will lead to actionable diagnostics and effective therapies. We are guided by our values of scholarly excellence; disruptive innovation; hands-on engineering/hacking/building; partnership and collaboration; open communication and respect; inclusiveness; and opportunity for all.

Our Vision                                                                     

• We pursue large scientific challenges that cannot be pursued in conventional environments
• We enable individual investigators to pursue their riskiest and most innovative ideas
• The technologies developed at Biohub facilitate research by scientists and clinicians at our home institutions and beyond

Diversity of thought, ideas, and perspectives are at the heart of Biohub and enable disruptive innovation and scholarly excellence. We are committed to cultivating an organization where all colleagues feel inspired and know their work makes an important contribution.

The Opportunity

The van der Stegen Lab at Biohub NY studies human immune cell development from induced pluripotent stem cells and designs engineering strategies to harness immune cells for therapeutic applications. We are looking for a Computational Biologist to join our team to further expand our evaluation of immune cell lineage commitment, function and how genetic engineering strategies can affect those. 

The Computational Biologist will possess deep expertise in the analysis of single cell transcriptional data, including developmental trajectory analysis, and ideally also have experience with proteomics datasets. They have an interest in hematopoiesis and immune cell biology and can demonstrate the intention to apply state-of-the-art analysis tools through close collaboration with the data science team at Biohub.

What You'll Do

• Implement and create analytical pipelines for transcriptomics, including chemical and/or genetic perturbations, and multi-omic datasets
• Support immunologists in experimental design for transcriptomic and multi-omic analysis
• Support immunologist in the experimental design of CRISPR screens
• Analyze scRNAseq, CITE-seq, scATACseq, TCR/BCRseq and Mass Spectrometry datasets
• Incorporate publicly available datasets with in-house generated datasets
• Support new hypothesis generation 
• Present research findings in academic journals and conferences

What You'll Bring

• PhD degree in computational biology, systems biology, immunology, bioengineering or a related field.
• Experience working with hematopoiesis-, immunology- or developmental biology-related datasets
• Experience analyzing data from perturbational screens (e.g. perturb-seq)
• At least 4 years of programming experience in R and/or Python
• Ability to communicate effectively with wet-lab biologists
• Expertise in bioinformatics including computational pipelines for analyzing bulk and single-cell genomics (Scanpy, Seurat, etc)
• Ability to work efficiently in HPC or cloud compute (e.g. AWS) environments
• Strong written and verbal communication skills
• Experience in presenting research findings
• Track record of publishing in peer-reviewed journals 
• 3+ years of experience with large scale immune data (single cell sequencing, T and B cell receptor profiling, mass spectrometry)
• Demonstrated ability to deliver multiple large biological data products, deploying QC best practices
• Experience with proteomic analysis datasets including flow cytometry and mass spectrometry
• Experience with spatial transcriptomics
• Familiar with metabolomic datasets
• Committed to writing well-commented code and documentation, and familiarity with coding best practices (i.e. version control, code review)

Compensation

The New York City, NY base pay range for a new hire in this role is $153,000 - $210,100. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

This position may be eligible to participate in Biohub's discretionary annual performance bonus program. Bonus eligibility and targets are determined in accordance with Biohub's total rewards philosophy and may vary by role.

Better Together

As we grow, we’re excited to strengthen in-person connections and cultivate a collaborative, team-oriented environment. This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in-office days determined by the team’s manager. The exact schedule will be at the hiring manager's discretion and communicated during the interview process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

If you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.

#LI-Onsite

The Team

Our AI research team sits at the heart of our mission to unlock new dimensions of biological understanding. You will leverage state-of-the-art AI to accelerate discovery and drive transformative insights in biology — developing novel AI models purpose-built for biological research, engineering robust systems that enable breakthrough science at unprecedented scale, and translating these advances into practical tools that empower researchers worldwide.

Our approach is comprehensive and integrated, bringing together world-class AI model development, exceptional engineering talent, high-quality biological data, powerful computing infrastructure, and strategic partnerships. Success requires excellence across five interconnected pillars: training frontier AI models specifically for biology; building engineering systems that maximize research velocity and efficiency; executing a sophisticated data strategy that fuels AI development; operating a world-class AI compute platform; and creating impactful products that transform AI capabilities into accessible scientific tools.

The Opportunity

This is an opportunity to shape the future of biological research by pushing the boundaries of what AI can achieve in science. You’ll work alongside leading experts in AI and biology, with the resources and mandate to tackle some of the most important questions in human health — advancing frontier AI research, accelerating engineering velocity, connecting rich biological data to AI systems, enabling reliable compute across environments, and translating models and data into usable, scalable applications that drive scientific impact.

The role is part of the Data team, which focuses on owning the strategy, sourcing and implementation for data supporting AI research and development. We're a small team with significant resources and long time horizons. Our goal is to maximize the speed, agility, and capability of biological AI research by connecting public data resources and Biohub's experimental platforms to AI systems. The data that trains biological frontier models comes in dozens of modalities (sequences, images, spatial coordinates, time series, molecular structures, metadata, publication artifacts) each with its own noise characteristics, biases, and information content. The question of how to represent this data for learning is one of the most important open problems in biological AI.

We’re looking for a data scientist with deep expertise in genomics (e.g., bulk and single-cell sequencing, functional genomics, CRISPR screens), who thinks creatively about data representation and tokenization, and can translate that thinking into novel training architectures. You’ll work across experimental, computational, and AI teams to build scalable, interpretable genomic data systems that power next-generation biological models and accelerate human health discovery. You will operate with broad scope and high autonomy, influencing roadmap decisions across teams, and mentoring senior individual contributors. Success in this role means scaling data systems that are not only large, but adaptive, interpretable, and scientifically grounded, accelerating progress toward robust biological frontier models and ultimately advancing human health.

What You'll Do

• Set technical vision and strategy for the design of data representations and tokenization strategies for diverse biological data types that enable novel model architectures.
• Define data standards and quality metrics that enable reliable cross-dataset integration and model-ready data products.
• Develop and validate approaches for combining heterogeneous data modalities into unified training frameworks, designing for robustness to noise, bias, and batch effects
• Evaluate how representation choices impact model performance, identifying which biological signals are captured or lost and iterating to improve
• Partner deeply with ML engineers and AI researchers to co-design datasets and feedback loops that optimize model training, evaluation, and generalization.
• Lead cross-functional initiatives spanning data engineering, infrastructure, science, and product, aligning technical execution with long-term scientific goals.
• Identify and drive new data acquisition and generation opportunities, from external collaborations to internal experimental pipelines.
• Serve as a technical mentor and leader, raising the bar for data science and ML rigor across the organization.

What You'll Bring

• PhD in computational biology, bioinformatics, or a quantitative biological field 
• 8+ years of experience working with large-scale biological datasets (genomics, epigenomics, transcriptomics, proteomics, or multi-omics), including ownership of end-to-end data products.
• Deep understanding of biological measurement types (sequencing, imaging, proteomics, or related), their underlying data characteristics, and how to transform raw data into ai-ready datasets.
• Experience designing data representations or feature engineering for machine learning in biomedical contexts
• Strong computational skills (Python, scientific computing libraries); Demonstrated ability to design robust, extensible data architectures and to evolve standards in fast-moving scientific domains.
• Strong expertise in machine learning and statistical modeling, with experience applying these methods to data quality assessment, automation, or decision-making systems. Familiarity with modern ML architectures (transformers, diffusion models, or similar) and how data representation choices affect learning
• Excellent communication skills, with the ability to translate between biology, ML, and engineering audiences.
• Creativity, Curiosity, scientific judgment, and a willingness to engage deeply with new biological domains and emerging AI paradigms.

Compensation

The Redwood City, CA  base pay range for a new hire in this role is $214,000 - $294,800. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

This position may be eligible to participate in Biohub's discretionary annual performance bonus program. Bonus eligibility and targets are determined in accordance with Biohub's total rewards philosophy and may vary by role.

Better Together

As we grow, we’re excited to strengthen in-person connections and cultivate a collaborative, team-oriented environment. This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in-office days determined by the team’s manager. The exact schedule will be at the hiring manager's discretion and communicated during the interview process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

If you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.

#LI-Hybrid 

We're looking for a Protein Design Scientist to own the development and deployment of agentic workflows for protein design. In this role, you will build systems that orchestrate protein language models, structure predictors, fitness scoring tools, and experimental feedback into automated or semi-automated design pipelines - closing the loop between computation and the wet lab.

This is a hands-on, high-ownership role. You'll work across the full stack of a design workflow: selecting and integrating models, defining agent logic and iteration strategies, building robust infrastructure for deployment, and collaborating closely with ML scientists, protein design scientists, and biologists to ensure your systems produce experimentally actionable results.

As an early employee, you will shape how Profluent approaches workflow automation and help define best practices for agentic systems in protein engineering.

Responsibilities

• Design, build, and deploy end-to-end agentic workflows that take protein function specifications and produce ranked candidate sequences for experimental validation
• Integrate protein language models, structure prediction tools, and scoring functions into multi-step pipelines with iteration, feedback loops, and human-in-the-loop checkpoints
• Own the full lifecycle of workflow systems: architecture, implementation, testing, deployment, monitoring, and iteration based on experimental outcomes
• Collaborate with ML scientists to evaluate and integrate new models into workflows, and with protein design scientists and biologists to translate scientific goals into computational specifications and ensure workflows align with experimental realities
• Develop tooling for experiment tracking, logging, reproducibility, and versioning of design campaigns
• Evaluate and benchmark workflow performance against experimental results, using outcomes to improve agent strategies and model selection
• Partner with ML scientists to identify where existing models fall short in agentic contexts and inform priorities for model development, fine-tuning, and evaluation

Qualifications

• PhD (or equivalent industry experience) in Computational Biology, Bioinformatics, Computer Science, Machine Learning, Biochemistry, or a related field
• Minimum of 3+ years of experience as a protein design scientist
• Strong software engineering skills: you write clean, modular, production-quality code (Python required; experience with workflow orchestration frameworks is a plus)
• Hands-on experience with protein language models (e.g., ESM, ProGen, ProtTrans) for sequence generation, scoring, or representation
• Demonstrated understanding of protein engineering principles: structure-function relationships, fitness landscapes, and how computational predictions connect to wet-lab validation
• Experience building multi-component systems that chain model inference with data processing, filtering, and decision logic

Preferences (but not required)

• Experience with agentic AI systems, LLM tool-use patterns, or multi-step reasoning pipelines
• Familiarity with structure prediction tools (AlphaFold, RoseTTAFold, ESMFold) and inverse folding methods (ProteinMPNN, LigandMPNN)
• Track record of computational designs that were experimentally validated
• Experience with cloud compute platforms (GCP, AWS, Azure) and containerized deployment (Docker, Kubernetes)
• Publications in protein design, protein engineering, or ML for biology at major conferences or journals
• Familiarity with directed evolution, rational design, or de novo protein design strategies

What We Offer 

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

The Position

At Maze Therapeutics, we believe precision medicine has the power to transform the lives of patients with both common and rare diseases. As a Machine Learning Application Engineer II, you will play a hands‑on role in delivering high‑impact, production‑grade solutions that advance our drug discovery programs. You will design, build, and scale data and machine learning infrastructure across early research, lead optimization, and development stages of the drug discovery pipeline. In this role, you will enable data‑driven science while upholding strong engineering standards and FAIR data principles. 

This position reports to a Senior Data Engineer. 

The Impact You’ll Have

• Support management of biobank scale datasets in Polaris, Maze’s internal platform supporting Compass, by building scalable data ingestion, cleaning, processing, and validation pipelines. 
• Work with scientific compute teams to design and deploy machine learning models to support workflows in research and small molecule drug discovery (compound property prediction, assay data prediction, data analysis). 
• Lead the evaluation and integration of Large Language Models (LLMs) to automate data ingestion workflows, enhance intelligent querying, and support user-facing variant association and scientific visualization platforms. 
• Design and operate scalable ML and data platforms leveraging Terraform (IaC) and Git-based CI/CD pipelines, incorporating workflow orchestration, automated model lifecycle management, and production-grade monitoring and reliability. 
• Collaborate with development organization to evaluate and deploy ML tools that support workflows across Regulatory, Clinical Operations, and Medical Affairs. 
• Collaborate cross-functionally translate scientific requirements into production-grade systems. 

What We’re Looking For

• Master’s degree in Computer Science, Machine Learning, Bioinformatics, Data Engineering, or related fields. 
• 3+ years of industry experience building production-grade data and ML pipelines, preferably in life sciences supporting drug discovery. 
• Hands-on experience deploying AI/ML models in drug discovery applications (e.g., computational biology/chemistry workflows). 
• Experience with FAIR data principles and strong programming skills in Python and SQL (R is a plus). 
• Proven experience in deploying and maintaining ML systems, including CI/CD, workflow orchestration, and monitoring. 
• Experience with workflow orchestration tools (e.g., Airflow, Prefect). 
• Experience with containerization and cloud infrastructure (Docker, Kubernetes, AWS or similar). 

About Maze Therapeutics

Maze Therapeutics is a clinical-stage biopharmaceutical company harnessing the power of human genetics to develop novel, small molecule precision medicines for patients living with renal, cardiovascular and related metabolic diseases, including obesity. The company is advancing a pipeline using its Compass platform, which allows it to identify and characterize genetic variants in disease and then link those variants to the biological pathways that drive disease in specific patient groups through a process it refers to as variant functionalization. The company’s pipeline is led by two wholly owned lead programs, MZE829 and MZE782, each of which represents a novel precision medicine-based approach for chronic kidney disease.  Maze is based in South San Francisco.

Our People

Maze is comprised of a team of passionate and creative professionals committed to discovering and delivering transformative medicines to patients suffering from both rare and common genetic diseases. We are fostering a culture that encourages vision, initiative and the development of talent. Our supportive work environment inspires creative thinking and freedom of expression, resulting in a stimulating atmosphere where people enjoy coming to work. While we have a passion for advanced science and pride ourselves on excellence in execution, ultimately, everything we do is about patients. 

Our Core Values

Further Together – Our path is paved with challenges, but with resilience and a team-first mentality, we’ll achieve our mission. 

Impact Obsessed – We embrace the bold, take calculated risks, and learn from our mistakes to improve the lives of others.

Stand True – Our integrity is foundational; it guides us no matter the obstacle.

The expected annual salary range for employees located in the San Francisco Bay Area is $154,000 - $188,000. Additionally, this position is eligible for an annual performance bonus.

Maze performs position-based compensation benchmarking to industry market data to ensure we pay competitive wages. Determination of starting salary will depend upon a variety of job-related factors, which may include professional experience, skills, and job location. The expected salary range for this role may be modified in the future.

Maze offers a robust benefits package to our eligible employees including competitive medical, dental, and vision insurance, mental health offerings, equity incentive plan, 401(k) program with employer match and a generous holiday and PTO policy.

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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 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