AI in Residence

AI in Residence is a highly selective role at the intersection of frontier machine learning and drug discovery. Designed as an industry alternative to a traditional postdoctoral position, the program is for exceptional researchers and engineers who want to apply advanced AI to real biomedical problems end to end, from data to deployed systems.

Residents join a small cohort working on high-impact AI efforts across Xaira. You’ll collaborate closely with AI scientists, research engineers, and drug discovery teams to design, build, and ship machine learning capabilities that directly influence therapeutic programs. This is hands-on, system-level work with real scientific consequence.

We’re looking for candidates with technical depth, intellectual independence, strong research judgment, and evidence of delivering high-quality work—whether through publications, open-source, or production systems.

What You’ll Do

• Develop and advance ML models for biological, preclinical, and translational datasets (e.g., multimodal omics, imaging, text, assay data)
• Design and implement scalable pipelines for data curation, training, evaluation, and inference integrated into discovery workflows
• Own projects end-to-end: problem framing → prototyping → validation → deployment
• Evaluate robustness and reliability (generalization, uncertainty, failure modes), plus interpretability where it supports scientific decision-making
• Contribute technical leadership by proposing new directions, shaping platform capabilities, and raising engineering/research standards through collaboration
  
  

You Might Work On

Examples include (not limited to):

• Foundation / representation models over multimodal biological and translational data
• Methods for small, biased, noisy datasets; distribution shift; and uncertainty estimation
• ML systems for experimental prioritization, assay interpretation, or translational signal discovery
• Evaluation frameworks and benchmarks tailored to discovery decision-making
• Tooling that makes models usable by scientists (interfaces, automation, monitoring)
  
  

What Success Looks Like

• You ship one or more models or pipelines that are used in real discovery workflows
• Your work improves decision quality (e.g., better prioritization, faster iteration, clearer uncertainty)
• You raise the bar on evaluation rigor and reproducibility (strong baselines, error analysis, reliable metrics)
• You leave behind maintainable systems (tests, documentation, monitoring) that others can build on
  
  

We Value

• Strong research judgment: choosing the right problems and knowing what “good evidence” looks like
• Rigor: careful experimental design, ablations, error analysis, and honest reporting
• Systems thinking: reliability, scalability, and maintainability—not just prototypes
  Clear communication: writing, documentation, and sharing decisions/assumptions
• Collaborative execution with scientific and engineering partners
  
  

Program Structure

Duration
6–12 months, with the possibility of extension or conversion to full-time

Start Dates
First hires beginning March 2026, with rolling applications and additional intakes in Summer and Fall 2026

Cohort Size
Small, highly selective cohort to enable meaningful ownership and close collaboration

Mentorship & Support
Dedicated technical mentor, plus structured feedback from senior AI, engineering, and scientific leadership

Publications & Presentations
We value scientific contribution and may support publications and conference presentations when appropriate. Publication scope and timing depend on project needs and are subject to internal review (e.g., IP and confidentiality). Authorship follows standard contribution-based guidelines.

Who Should Apply

We encourage applications from candidates who meet most of the following:

• Recent MS or PhD graduates (or equivalent research experience) in ML/AI, computational biology, biomedical engineering, or related fields
• Evidence of research excellence through high-quality publications or artifacts. Top venues (e.g., NeurIPS, ICML, ICLR, CVPR, ACL; Nature Methods, Cell Systems) are a plus, but strong preprints, open-source contributions, or shipped systems with demonstrated impact are equally compelling
• Demonstrated ability to lead substantial technical work with originality—new modeling ideas, rigorous experiments, or production-grade systems adopted by others
• Motivation to translate rigorous research into reliable, deployable AI systems that support therapeutic discovery
  
  

Please include a brief cover letter describing your interest in this role, why you’re excited about this area, and what you hope to gain from the experience.

Compensation:

The expected monthly compensation range is $10,000–$15,000, depending on experience and qualifications. We are open to higher compensation for candidates with exceptional experience or impact.

• Develop multimodal foundation models spanning image and molecular data
• Design approaches that unify representation learning and generative modeling
• Train large-scale models on structured, high-dimensional datasets
• Explore cross-modal alignment, prediction, and generation
• Build scalable systems for data processing, training, and evaluation
• Work in a research-driven environment with evolving problem definitions

• Experience with representation learning (self-supervised, contrastive, masked modeling, etc.)
• Experience with generative modeling (diffusion, autoregressive models, VAEs, or related approaches)
• Proficiency in Python, ML frameworks, and CI/CD (PyTorch, JAX, etc.)

• Work on multimodal learning or cross-domain representation learning
• Experience with image data, molecular / omics-like data, or both
• Familiarity with large-scale training

• Exposure to biological or scientific datasets
• Experience with paired or partially aligned multimodal data
• Comfortable working in open-ended, evolving problem spaces

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 $170,000 - $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.

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.

Role Overview
The Senior Director, Supply Chain and Strategic Sourcing will lead and integrate Xaira’s supply chain, procurement, and contract governance functions, ensuring reliable access to the external partners, platforms, and services that support Research, Biomedical AI, Platform Engineering, and Corporate teams.

This role is responsible for establishing disciplined sourcing strategy, strengthening vendor management, building contract governance infrastructure, and ensuring operational continuity across critical suppliers and service providers. The individual will provide strategic oversight while elevating two existing functions, procurement and contracts, into a cohesive, scalable supply chain capability.

Operating at the intersection of research, technology infrastructure, and external partnerships, This role is responsible for bringing strategic focus to how Xaira engages its external partners, ensuring that sourcing, vendor, and contract decisions serve the company's mission, growth, and long-term goals

Key Responsibilities

Supply Chain Leadership

• Develop and lead overall supply chain strategy
• Ensure continuity, reliability, and risk mitigation across critical vendors and external partners
• Oversee vendor selection, onboarding, performance monitoring, and renewal planning
• Provide leadership with visibility into external dependencies and operational risk exposure
• Map and monitor critical vendor dependencies across research services, cloud infrastructure, data providers, and platform suppliers

Strategic Sourcing

• Guide category strategy development across cloud infrastructure, AI/ML platforms, research services, data providers, lab suppliers, and corporate systems
• Oversee competitive sourcing processes and major vendor negotiations
• Ensure cost discipline and long-term value across supplier relationships
• Partner with Finance to strengthen forecasting, budget alignment, and spend transparency

Contracts and Governance

• Oversee contract negotiation and execution standards across MSAs, SOWs, SaaS agreements, data licenses, and research vendor agreements.
• Ensure structured intake, review, and lifecycle management processes are followed
• Establish clear governance for renewals, amendments, and contractual obligations
• Strengthen coordination between Legal, Finance, and operational stakeholders
• Build contract architecture that gives Legal and leadership a strategic view of risk

Leadership

• Lead and develop procurement and contracts team members
• Establish performance expectations, KPIs, and operating cadence
• Build scalable systems and processes appropriate for company growth
• Elevate supply chain operations from reactive processing to a strategic operational partner

Core Capabilities

• Supply Chain Integration and Operational Continuity
  Ability to ensure reliable supply and vendor performance across research services, cloud infrastructure, laboratory suppliers, and external partners while identifying and mitigating operational risks before they impact the organization.
• Advanced Strategic Sourcing and Negotiation
  Demonstrated ability to structure and lead complex negotiations across cloud infrastructure, software platforms, research services, and vendor agreements while balancing cost, flexibility, speed, and long-term value.
• Contract Architecture and Governance Design
  Ability to design and implement structured contract frameworks, approval workflows, and lifecycle management processes that create visibility, enforce standards, and reduce legal and financial exposure.
• Financial Stewardship and Vendor Risk Management
  Strong analytical capability to model vendor spend, forecast commitments, evaluate total cost of ownership, and proactively surface financial and operational risk.
• Cross-Functional Partnership and Organizational Influence
  Ability to align Legal, Finance, Research, and Engineering stakeholders around sourcing strategy, vendor commitments, and contractual decisions while balancing operational needs and risk management.

Qualifications

• 10+ years of experience in supply chain, procurement, or strategic sourcing leadership
• Experience operating in biotech, life sciences, or technology-driven R&D environments
• Demonstrated experience managing vendor ecosystems spanning cloud infrastructure, SaaS platforms, research services, or technical R&D environments
• Prior responsibility for leading both sourcing and contract management functions
• Proven ability to build structure and operational discipline in growth-stage organizations
• Strong financial acumen, vendor risk management capability, and negotiation experience

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 $215,000 - $280,000 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.

About the Role

The Senior Director, Project Management, will lead cross-functional execution of the company’s most complex scientific and platform initiatives, ensuring work across biology, computational science, protein design, and engineering teams progresses with clarity, alignment, and momentum.Working closely with scientific and technical leadership, this individual translates strategic priorities into well-structured projects with clear scope, milestones, ownership, and dependencies. The role requires strong project management discipline combined with a product lens, helping teams prioritize work based on impact, define clear outcomes, and focus effort on the highest-value initiatives.Operating at the center of scientific, technical, and organizational execution, this leader brings structure to complex work while enabling teams to move quickly in a discovery-driven environment.

Key Responsibilities
Project Leadership

• Lead planning and execution of complex, cross-functional projects spanning research, computational science, protein design, and engineering teams
• Translate strategic priorities into clearly structured projects with defined scope, timelines, ownership, and success criteria
• Apply a product lens to project leadership, ensuring initiatives are prioritized based on impact, feasibility, and organizational goals
• Partner with scientific and technical leaders to define clear outcomes and success criteria rather than activity-based workstreams
• Manage scope intentionally, balancing scientific exploration with disciplined execution
• Identify risks early and implement mitigation strategies to maintain project momentum

Strategic Execution Partnership

• Partner with scientific and technical leadership to translate organizational priorities into executable project plans
• Help shape the sequencing of major initiatives to ensure resources are focused on the highest-impact work
• Provide leadership with clear visibility into progress, dependencies, and emerging execution risks across projects
• Frame execution progress, tradeoffs, and emerging risks in ways that enable leadership to make timely and informed decisions

Cross-Functional Alignment

• Align stakeholders across biology, computational science, protein design, and engineering teams around shared priorities and sequencing of work
• Coordinate interdependent projects across research and platform teams, ensuring work is sequenced appropriately and dependencies are clearly understood
• Identify points where progress in one initiative enables or constrains work in another, helping teams adjust plans accordingly
• Resolve cross-team bottlenecks and maintain forward momentum across projects

Project Operating Model

• Establish consistent project planning, tracking, and reporting practices across teams
• Introduce planning frameworks and decision rhythms that improve transparency and coordination
• Evaluate, select, and harmonize project management tools and platforms across the organization, ensuring teams operate with a consistent and scalable PM infrastructure
• Strengthen the organization’s ability to execute complex scientific and technical initiatives predictably

AI-Enabled Project Management

• Champion the integration of AI tools and workflows into project management practices, identifying opportunities to improve planning, tracking, risk identification, and reporting through intelligent automation
• Stay current on emerging AI capabilities relevant to PM operations and serve as an internal advocate for thoughtful, effective adoption across teams
• Partner with computational and engineering teams to ensure AI-driven initiatives are managed with appropriate rigor while leveraging AI to enhance the PM function itself

Team Leadership

• Build and develop a high-performing project management team as the organization grows
• Establish expectations for rigor, clarity, and accountability in project execution
• Mentor project managers to operate as strategic partners to scientific and technical leaders
• Define team structure, hiring priorities, and development pathways that scale with organizational growth
• Foster a culture of continuous improvement within the PM team, regularly evaluating and refining how the team operates

Core Capabilities

• Complex Project Execution - Demonstrated ability to lead large, cross-functional projects involving multiple stakeholders, dependencies, and evolving scientific priorities.
• Product-Oriented Thinking - Ability to approach project leadership with a product mindset—prioritizing work based on impact, defining clear outcomes, managing scope intentionally, and ensuring initiatives deliver meaningful value.
• Cross-Functional Leadership - Proven ability to align scientific, technical, and operational teams around shared priorities and drive execution through influence.
• Structured Planning and Risk Management - Strong capability in dependency mapping, risk identification, mitigation planning, and maintaining forward progress in complex environments.
• Executive Communication and Decision Framing - Ability to synthesize complex scientific and technical work into clear updates, priorities, and tradeoffs that support effective leadership decision-making.

Qualifications

• Bachelor’s degree required; advanced degree preferred (MBA, MS, PhD, or equivalent)
• 10+ years of experience leading complex cross-functional projects in biotech, TechBio, or similarly interdisciplinary environments where computational and experimental research intersect.
• Strong understanding of AI/ML-enabled biological research, with experience partnering closely with computational biology, protein design, biomedical AI, or research engineering teams.
• Experience working closely with scientific and engineering teams in research or platform settings
• Deep understanding of drug development processes, including preclinical through early clinical stages, with the ability to connect research and platform initiatives to the broader development continuum
• Demonstrated ability to bring structure and clarity to complex initiatives in fast-moving organizations
• Strong organizational, communication, and stakeholder alignment skills
• Proven ability to influence highly skilled teams without relying on formal authority
• Experience managing and developing high-performing teams

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 $225,000 - $285,000 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.

About the Role
We are seeking a scientific leader to serve as our Director of Biomarkers and Experimental Medicine. This role will create and execute biomarker strategies across discovery and early development, grounded in human biology and designed to scale from target-agnostic disease understanding through program-specific development. You will work closely with Biomedical AI to use multi-modal human data to identify biomarker signals, define patient hypotheses, and establish biomarkers that guide indication choices, patient selection, and proof-of-biology.

A core part of the role is building biomarker capability before programs fully crystallize. This includes defining disease-state and patient stratification frameworks, developing assay and data standards, and creating a biomarker toolkit that can be applied as targets emerge.

Key Responsibilities

• Help create and execute strategies and incorporate human patient data to build AI models for patient stratification, target validation and biomarker discovery, in conjunction with a cross-functional team of experts including Biomedical AI
• Establish a target-agnostic biomarker strategy that defines disease biology, patient subgroups, and measurable signals of disease state, progression, and response potential, even before a specific therapeutic target is selected.
• Define biomarker hypotheses and evidence plans that connect human biology to program direction, including how biomarkers will influence indication strategy, cohort definitions, and clinical readiness.
• Work closely with Biomedical AI/ML to translate biomarker questions into ML-ready problem definitions, including cohort definitions, endpoints, labels, success criteria, and validation expectations.
• Identify and prioritize AI/ML model outputs needed for biomarker work, including patient segmentation, biomarker signal models, multi-modal integration, and response or outcome prediction where appropriate.
• Lead assay strategy and readiness planning, including platform choices, fit-for-purpose validation, sample strategy, and decision points that allow teams to act on biomarker results.
• Create standards for biomarker and model quality, reproducibility, and documentation so outputs are decision-grade and usable across programs.
• Build biomarker data assets and workflows that scale, including reference cohorts, baseline datasets, and repeatable analyses that can be reused as targets and indications evolve.
• Drive cross-functional alignment so biomarker insights consistently inform discovery priorities, program selection, and early development planning.
• Establish and manage an external network of biomarker experts, clinical and translational advisors, and key opinion leaders to pressure-test strategy and strengthen clinical relevance.

Qualifications

• PhD, MD, or MD/PhD with 8+ years of experience in biomarkers, translational science, or human biology within biotech or pharma.
• Deep expertise in biomarker discovery and development, including experience defining biomarker strategies that support program decisions and differentiation.
• Strong experience with human data and multi-modal biology, including genetics and omics, and comfort operating when targets and programs are still being defined.
• Demonstrated ability to work closely with AI/ML teams and translate biomarker questions into ML-ready problem definitions and model development plans.
• Track record of building biomarker capabilities and standards in early-stage environments, including assay readiness, evidence planning, and cross-functional execution.
• Excellent communication and scientific judgment, with the ability to drive clear decisions from complex data, and work collaborative in multidisciplinary teams.

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 $196,000 - $245,000 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.

About the Role
We are seeking a Biomedical AI Engineer to design and deploy agentic AI systems that can reason over biomedical knowledge, plan multi-step analyses, and autonomously integrate diverse scientific data sources to accelerate therapeutic discovery.

This role goes beyond traditional LLM + RAG pipelines. You will build AI agents that can retrieve, synthesize, evaluate, and act on biomedical information across literature, omics datasets, and clinical records operating as intelligent systems embedded within discovery workflows.

Key Responsibilities

• Design and implement agentic AI architectures capable of multi-step reasoning, planning, and tool use in biomedical contexts.
• Develop LLM-based agents that dynamically retrieve, rank, and synthesize knowledge from scientific literature, knowledge graphs, omics datasets, and clinical data.
• Build memory and feedback mechanisms that allow agents to refine hypotheses, update context, and adapt to evolving data.
• Integrate external tools (analysis pipelines, simulation engines, statistical models, databases) into autonomous agent workflows.
• Architect scalable systems that combine structured and unstructured biomedical data within production-grade AI environments.
• Collaborate closely with computational biologists, translational scientists, and software engineers to embed agentic systems into real-world discovery pipelines.
• Evaluate robustness, reliability, and interpretability of autonomous systems in high-stakes biomedical settings.

Qualifications

• Degree in Computer Science, Machine Learning, Computational Biology, Biomedical Informatics, or related field.
• Strong hands-on experience with large language models, including fine-tuning, alignment, and structured prompting.
• Experience building agent-based systems or complex LLM orchestration frameworks (e.g., multi-agent systems, tool-using LLMs, planning modules).
• Proficiency in Python and modern ML frameworks (PyTorch, JAX, TensorFlow).
• Experience working with large-scale biomedical datasets (genomics, transcriptomics, clinical records, or scientific corpora).

Preferred

• Experience designing autonomous research assistants or AI systems that perform multi-step scientific reasoning.
• Familiarity with knowledge graphs, hybrid symbolic-neural systems, or multimodal foundation models.
• Understanding of privacy, security, and regulatory considerations in healthcare AI.

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 $190,000 - $280,000 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.

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 highly motivated and experienced Head of Research to lead our early discovery research group of talented Principal Investigators and their laboratory teams. This role will be critical in developing research strategies, evaluating research progress, and advancing our early stage drug discovery pipeline for improving healthspan by developing new therapeutics for aging and aging-related diseases. We seek expertise in applying cutting-edge biochemical, molecular, and cell biological techniques, including microscopic and "omics" technologies, to unlock the complexities of aging physiology. Experience in moving projects from early discovery research to translational drug development will be important. 

Join our collaborative, cross-functional environment at the forefront of aging research, work alongside world-class technology labs, lead ambitious research projects that transform our understanding of aging, and develop innovative therapeutics for aging and aging-related diseases.

Responsibilities:

• Manage a group of Principal Investigators with ambitious research programs
• Lead an independent research effort aimed at gaining valuable insights into aging biology
• Provide scientific direction, including clinical and biological insights, for a broad range of translational projects
• Recruit top talent with aging research as a key focus
• Join Calico’s Scientific Review Committee and other leadership functions
• Contribute substantively, through leadership and research, to Calico’s ambitious research efforts to understand the fundamental biology of human aging and discover mechanisms that contribute to human longevity, as a basis for devising interventions

Position Requirements:

• MD/PhD, PhD or equivalent degrees in molecular and cellular biology, immunology, neurobiology, structural biology, or related fields with 15 or more years of postdoctoral and/or industry experience in the area of drug development and/or basic biomedical research, especially in aging or aging-related diseases
• Rising or proven leader in academia or industry 
• Creative and critical thinking skills
• Strong interpersonal communication skills, both verbal and written
• Success in managing and mentoring other scientists and research programs
• Strong record of creative scientific achievements as evidenced by impactful publications, patents (or applications), and national or international recognition
• Technical expertise in technologies related to basic or translational biomedical research
• Must be willing to work onsite five days a week, except for conferences or off-site work-related meetings

The estimated base salary range for this role is $314,000 - $360,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.

We’re looking for a Hardware R&D Research Intern to join our Research Operations team in San Francisco, with a dedicated focus on hardware research programs. Our Research Operations team designs and executes the human research studies that power Oura’s next-generation sensor development and scientific innovation and bolster our scientific credibility. The focus of the hardware research program is to develop and validate new features and continue to enhance the accuracy of our algorithms.

As a Hardware R&D Research Intern, you’ll support internal and external human research studies that help develop and validate new Oura hardware and sensing capabilities. You’ll get hands-on experience across the study lifecycle — from equipment prep and lab setup to data collection and data quality checks.

This is a full‑time summer internship based in San Francisco, CA, with on‑site work required 5 days/week for data collection and lab activities. The internship duration is 3–4 months, with flexible start and end dates between May and September 2026.

What you will do

• Support hardware‑focused human studies: Assist with 1-2 hardware and sensing research studies under the guidance of Research Coordinators and Research Project Managers.
• Prepare and maintain research equipment
• Assist with setting up research equipment for both internal and external hardware research studies.
• Perform equipment checks before sessions (battery status, firmware/app versions, connectivity, storage).
• Help track and organize research equipment inventory, including labeling, storage, and basic troubleshooting.
• Support study documentation and data quality checks
• Contribute to protocols, standard operating procedures (SOPs), and checklists for study visits and equipment handling
• Assess and flag quality concerns related to device signals (e.g., missing data, motion artifacts, device non‑wear, connectivity issues)
• Contribute to simple data review summaries (e.g., dashboards, spreadsheets) to monitor study progress
• Collaborate with cross‑functional partners (e.g., Research Operations, Hardware, Data Science) to keep documentation organized and up to date

Requirements:

We’d love to hear from you if you are a current undergraduate student who:

• Is studying biomedical engineering, electrical engineering, human biology, neuroscience, physiology, computer science, or a related field
• Has experience or coursework related to human subjects research, lab work, or experimental design
• Is excited about a future career in wearable technology, sensors, and hardware R&D
• Is comfortable working hands‑on with electronic devices and lab or test equipment
• Demonstrates strong attention to detail and a commitment to high‑quality documentation
• Is proficient with Google Workspace tools and comfortable using iOS and/or Android devices
• Is based in or able to be in San Francisco, CA for the summer and available for regular on‑site work for data collections

This is a paid opportunity to work with a dynamic team and gain valuable experience in the health tech industry. You will also receive an Oura Ring of your own to keep. Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

• Compensation range: Region 1: $33-$36/hr 

If you're interested in this opportunity, please submit your resume and cover letter for consideration.

POSITION SUMMARY:

B Capital is looking for a pre-MBA Associate for the Healthcare AI Team who has an incredible drive to assist in the investment process from end-to-end on investments from Series A to Growth Equity. Primary responsibilities will be helping identify new healthcare investment opportunities through research-driven sourcing, researching markets and sector trends, evaluating deals, and conducting detailed business and financial due diligence, including complex financial models.  The individual will work across healthtech and digital health.  The role requires a background in finance, familiarity with AI, and maturity, flexibility, intellectual curiosity, and a proven track record of turning ideas into action.

BASIC JOB RESPONSIBILITIES:

Market research

• Develop market research and investment theses to guide sourcing efforts.
• Source new investment opportunities based on investment themes and research.
• Follow AI trends in healthcare

Deal screening and evaluation

• Evaluate and assess the viability of investment materials we receive from potential companies.
• Lead key pieces of diligence on investment opportunities and deal processes (e.g., audit, tax, legal, financial modeling, etc.).

Building company value

• Deliver high-touch support to our portfolio companies across a number of operating areas.
• Utilize the firm’s and BCG’s networks to connect companies with the highest value customer targets.

BASIC JOB REQUIREMENTS:

• Passion for disruptive technology.
• 1-3+ years of relevant work experience strongly preferred (e.g., investment banking on a healthcare team or work on a finance or BD team in an operating role)
• An undergraduate degree in economics, data science, biology, biomedical engineering, engineering with biology, biochemistry, or other relevant fields is highly desired.
• Excellent quantitative and qualitative analytical skills.
• Prior VC/PE investing experience not required, but a plus.  Finance experience is highly desired.
• The role will be based in San Francisco, and you must be comfortable relocating or presently be based in SF
• Hybrid Work (3 days in SF office) 

 KEY COMPETENCIES:

The ideal candidate has strong analytical abilities and is intellectually curious – particularly in terms of new and emerging technologies.

• Awareness of the market and a perspective on potential investable market trends, particularly in AI related approaches.
• Experience distilling ideas and insights into clean, digestible formats (e.g., slides, documents) required.
• Experience with detailed financial modeling, including P&L, balance sheet, and cash flow statements, as well as quantitative market research (e.g., valuation comps) required.
• Exposure to core venture capital “math” skills (e.g., cap table, returns modeling) and familiarity with standard venture terms and concepts is a plus.
• Entrepreneurial spirit to help us shape new portfolio investments and our own company.
• Exceptional interpersonal skills, business judgment, and work ethic.

ABOUT B CAPITAL

B Capital invests globally in extraordinary founders and businesses shaping the future through technology. With approximately $10 billion in assets under management and dedicated stage-based funds, the firm focuses on seed to early- and late-stage venture growth investments, primarily in the technology, healthcare and resilience tech sectors. Founded in 2015, B Capital has an integrated, global team across nine locations in the U.S. and Asia. The firm’s value-add platform, together with the consulting expertise of its strategic partner, The Boston Consulting Group, provides entrepreneurs with the tools and resources to scale quickly and efficiently, expand into new markets and build market-leading businesses. For more information, click here.

B CAPITAL GROUP CORE VALUES:

• Generosity: We’re collaborative and always willing to share our time and knowledge.
• Resilience: We’re persistent and determined to succeed, persevering through challenges and seeing change as an opportunity.
• Open-mindedness: We’re curious and welcoming. Our global perspective and commitment to diversity, equity, and inclusion make our culture stronger and more innovative.
• Will: We believe in the companies we’ve invested in and we’ll do everything in our power to help them change the world for the better.
• Teamwork: We value our relationships above all. We work hard to build trust and respect with founders, investors, partners and colleagues.
• Humility: We add value by going beyond for founders and LPs. We strive to let our work speak for itself.

B Capital Global US LLC is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, national origin, disability, protected veteran status, or any other characteristic protected under federal, state or local law.

The salary range is $110,000-$130,000 and will be commensurate with relevant experience.

Salary Range applies to California candidates only. The actual salary may be subject to change. 

About the Position

We're looking for a Senior Data Engineer to join the Scientific Data Intelligence (SDI) team at Formation Bio to help transform Real World Data (RWD)—spanning electronic health records, claims, and other longitudinal patient data sources—into structured, analytics-ready assets. In this role, you'll be partnering closely with our Data Science team not only to model and transform data, but also to actively analyze it: answering research questions, generating evidence, and supporting scientific decision-making across our drug portfolio.

This position sits at the intersection of healthcare data engineering, real-world evidence analysis, and generative AI. While a strong foundation in building reliable, scalable pipelines is essential, you'll be equally expected to roll up your sleeves and work directly with the data—constructing cohorts, running analyses, and translating findings into actionable insights for scientific and business stakeholders.

The ideal candidate is a hybrid of data engineer and applied scientist: someone who can build the infrastructure and then use it, with familiarity in RWD study design, GenAI fluency (e.g., LLM-based entity extraction, summarization, classification), and strong technical expertise with modern data tooling. You'll play a key role in shaping how real-world patient data becomes discoverable, structured, and impactful across the organization.

Responsibilities

• Model and transform raw EHR and claims data into clean, canonical, and analytics-ready datasets using SQL, Python, and clinical standards like OMOP.
• Build and manage scalable data pipelines using Dagster for orchestration, dbt for transformation, and Snowflake as the primary compute and storage engine.
• Conduct hands-on RWD analyses to answer scientific and strategic research questions—including disease epidemiology, treatment patterns, patient journey characterization, and comparative effectiveness.
• Partner with Data Scientists and clinical leads to design and execute observational studies, translating scientific questions into well-structured, reproducible analyses.
• Implement data validation, completeness, and observability frameworks to ensure real-world datasets are accurate, comprehensive, and trustworthy for downstream research and product use.
• Apply Generative AI techniques within transformation and analysis layers to accelerate data structuring and insight generation.
• Communicate findings clearly to both technical and non-technical stakeholders, including summaries for portfolio teams and leadership.

About You

• You have 5+ years of experience in data engineering, ideally with at least 2 years working in healthcare or life sciences, including direct exposure to EHR or claims datasets.
• You have experience with ontologies and biomedical schemas (e.g. UMLS, LOINC, ICD9/10, MeSH) and understand the modalities found within RWD — billing claims, lab results, visit notes.
• You're fluent in SQL and Python, and you've built and maintained production-grade pipelines that support analytics or scientific workflows.
• You have experience building longitudinal patient cohorts from EHR or claims data, including index date logic, washout periods, and follow-up window construction.
• You have a solid understanding of the causal inference frameworks such as potential outcomes and target trial emulation. 
• You have working familiarity with real-world evidence study design concepts—such as active comparator new user designs, time-to-event outcomes, confounder adjustment, and causal discovery algorithms—sufficient to partner effectively with Data Scientists on causal inference workflows.
• You value clarity, documentation, and structured thinking—especially when working with complex healthcare data.
• You have hands-on expertise with modern data infrastructure, such as Snowflake, dbt, and Dagster.
• You can balance upfront design with speed to execution, slowing down when it counts without getting stuck in the details.
• Bonus: You've worked in regulated or privacy-sensitive data environments and are familiar with governance models for PHI or sensitive data.
• Bonus: You have prior experience working with commercial RWD vendors (e.g. Truveta, Optum, Komodo, IQVIA) and understand the nuances of licensed claims and EHR datasets, including longitudinal patient journey construction and line-of-therapy sequencing.

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

About the Position

We're looking for a Data Engineer to join the Scientific Data Intelligence (SDI) team at Formation Bio to help build and scale the data infrastructure that powers our drug development platform. In this role, your primary focus will be supporting the Data Science team — building the coherent, well-structured data models, feature engineering pipelines, and evidence layers that underpin their scientific work. You'll also be responsible for ingesting data from a wide variety of sources—APIs, files, databases, and licensed third-party datasets—and transforming it into clean, analytics-ready assets using modern data tooling.

This is a foundational engineering role for someone who takes pride in building things right: reliable pipelines, well-structured data models, and systems that others can trust and build on. You'll work closely with Data Scientists and other engineers across the SDI team to ensure that high-quality data is consistently available where and when it's needed — and structured in a way that directly accelerates scientific discovery.

The ideal candidate is deeply fluent in Snowflake and dbt, has strong opinions about data modeling best practices, and has experience handling large and complex datasets across diverse ingestion patterns. You thrive in environments where data quality and engineering rigor are treated as first-class concerns.

Responsibilities

• Partner closely with Data Scientists and other teams to build coherent data models, feature engineering pipelines, and structured evidence layers that directly support scientific analysis and machine learning workflows.
• Design and build scalable ingestion pipelines to onboard data from diverse sources including REST APIs, flat files, relational databases, and licensed third-party datasets.
• Develop and maintain robust data models in dbt, adhering to best practices around modularity, testing, documentation, and layered architecture (staging, intermediate, mart).
• Orchestrate pipelines using Dagster to ensure reliable, observable, and maintainable workflows.
• Implement data quality checks, validation frameworks, and monitoring to ensure trustworthiness of datasets across the platform.
• Collaborate with Data Scientists and analysts to understand data needs and translate them into well-structured, reusable models.
• Handle large-scale data movement and transfer scenarios, applying appropriate tooling and patterns to ensure efficiency and reliability at scale.
• Document data models, pipeline logic, and transformation assumptions to support discoverability and data governance.

About You

• You have 5+ years of experience in data engineering, with a strong track record of building and maintaining production-grade pipelines.
• You are deeply fluent in dbt and follow best practices rigorously—including modular model design, sources and refs, testing (schema + data), documentation, and environment management.
• You have hands-on expertise with Snowflake, including schema design, performance tuning, and data governance patterns.
• You have experience with at least one modern orchestration tool—we use Dagster, but experience with Airflow or Prefect is equally welcome.
• You have broad ingestion experience across source types: REST APIs, flat files (CSV, JSON, Parquet), relational databases, and vendor-licensed datasets.
• You have worked with large datasets (TB -> PB scale) and understand the engineering considerations that come with scale—partitioning, incremental loading, efficient data movement, and storage optimization.
• You're a strong data modeler who thinks carefully about how data is structured, named, and layered for downstream usability.
• You value documentation, testability, and building things others can maintain and extend.
• You can balance upfront design with speed to execution, slowing down when it counts without getting stuck in the details.
• Bonus: You have experience with data quality and observability tooling such as Elementary, Great Expectations, or similar frameworks — and you treat data quality as a first-class engineering concern, not an afterthought.
• Bonus: You have experience with Spark, Databricks for large-scale data processing workloads.
• Bonus: You have experience with large-scale data transfer tooling such as AWS DataSync, AWS S3 Transfer Acceleration, or equivalent cloud-native data movement services.
• Bonus: You have experience in healthcare or life sciences data environments, including familiarity with EHR, claims, or other biomedical datasets.

Total Compensation Range: $177,500 - $232,000

As the Senior Device Quality Engineer, you will serve as a key technical lead for software quality and design excellence. You will bridge the gap between rapid Agile development and rigorous medical device regulations, ensuring that our digital health solutions—including Software as a Medical Device (SaMD) and AI/ML-enabled technologies—are safe, secure, and compliant.

Your core responsibility will be the hands-on management of the end-to-end design control process within Heartflow’s Software Development Lifecycle (SDLC). You will ensure that software architecture, security, and global regulatory requirements are integrated into every release.

Key Responsibilities

Technical Leadership

• Standards Execution: Apply global regulatory standards, including IEC 62304, IEC 82304, ISO 14971, ISO 13485, and AAMI TIR45, to daily development activities.
• SDLC Support: Implement validation frameworks for AI/ML, Cloud Infrastructure (SaaS), and Cybersecurity (ISO 81001-5-1) within the Quality Management System (QMS).
• Agile Integration: Partner with engineering teams to execute "Compliance at Speed," ensuring Agile sprints meet all regulatory rigor and result in high-quality, predictable releases.

Design Quality & Risk Management

• Design Reviews: Participate in software architecture reviews to ensure the implementation of safety-by-design and privacy-by-design principles.
• Risk Analysis: Facilitate and document comprehensive risk management activities, including Hazard Analysis, Fault Tree Analysis (FTA), and Software FMEAs.
• V&V Execution: Act as the lead for Software Verification and Validation (V&V); develop and execute test strategies, protocols, and reports to ensure product performance.

Execution & Compliance

• DHF Ownership: Manage the Design History File (DHF) from concept to commercialization, ensuring all documentation is audit-ready and design transfer is seamless.
• Audit Support: Support the organization during internal and external audits (e.g., FDA, Notified Body, MDSAP) as a subject matter expert for software processes.

Cross-Functional Collaboration

• Technical Documentation: Support Regulatory Affairs in authoring technical files for global submissions, including FDA (510k/De Novo), PMDA, and EU-MDR.
• Team Guidance: Provide technical coaching and quality training to R&D and Product teams to foster a culture of compliance.

Skills Needed

• Strong critical thinking skills and great attention to detail.
• Ability to work as a self-starter in a fast-paced, adaptive environment.
• Excellent communication, documentation, and time management skills.

Educational Requirements & Work Experience

• Bachelor’s degree in Software Engineering, Computer Science, Biomedical Engineering, or a related technical field is required.
• 5–8 years of experience in quality engineering or product development within the medical device industry.
• Certifications (Preferred): ASQ Certified Quality Engineer (CQE), Certified Software Quality Engineer (CSQE), or Green Belt.

This position has an estimated base salary of $160,000 - $180,000, bonus. #LI-IB1; LI-Hybrid

As the Senior Manager, Device Quality Engineering, you will lead the global strategy for software quality and design excellence. You will be responsible for building and managing a high-performing team that bridges the gap between rapid Agile development and rigorous medical device regulations. Your leadership ensures that our digital health solutions—including Software as a Medical Device (SaMD) and AI/ML-enabled technologies—are safe, secure, compliant, and scalable.

Your core responsibility will be the strategic oversight of the end-to-end design control process within the Software Development Lifecycle (SDLC). You will define the roadmap for compliance, security-by-design, and global regulatory readiness while mentoring the next generation of quality engineering leaders.

Key Responsibilities

Strategic Leadership & Team Management

• Departmental Authority: Serve as the primary leader and organizational authority on global regulatory standards, including IEC 62304, IEC 82304, ISO 14971, ISO 13485, and AAMI TIR45.
• QMS Roadmap: Drive the evolution of the Quality Management System (QMS), establishing the vision for validation frameworks involving AI/ML, Cloud Infrastructure (SaaS), and Cybersecurity (ISO 81001-5-1).
• People Leadership: Recruit, mentor, and develop a team of quality engineers, fostering a culture of "Compliance at Speed" through Agile best practices.
• Release Accountability: Ensure predictable, complete, and high-quality releases by managing resource allocation and departmental throughput.

Design Quality & Risk Governance

• Architectural Oversight: Direct the review of software architecture to ensure the implementation of safety, security-by-design, and privacy-by-design across all product lines.
• Risk Management Governance: Oversee comprehensive risk management activities, ensuring consistency across Hazard Analysis, Fault Tree Analysis (FTA), and FMEAs for software-driven failure modes.
• V&V Strategy: Act as the final authority for Software Verification and Validation (V&V) strategies; ensure protocols and reports meet the highest standards of robust product performance.

Execution & Compliance

• DHF Lifecycle Management: Ensure organizational compliance from concept to commercialization by governing the Design History File (DHF) and design transfer processes.
• Audit Leadership: Lead the organization’s representation during internal and external audits and inspections (e.g., FDA, Notified Body, MDSAP).

Cross-Functional Collaboration

• Regulatory Partnership: Partner with Regulatory Affairs leadership to strategize and approve technical documentation for global submissions, including FDA, PMDA, and EU-MDR.
• Executive Influence: Provide technical guidance and status updates to R&D, Product, and Program Management executives.

Skills Needed

• Leadership Excellence: Proven ability to manage teams, develop talent, and influence cross-functional stakeholders.
• Strategic Thinking: Strong critical thinking skills with the ability to balance long-term quality goals with immediate business needs.
• Adaptability: Ability to lead a department in a fast-paced, adaptive environment.
• Communication: Exceptional communication and documentation skills, with the ability to translate complex technical risks into business impact.

Educational Requirements & Work Experience 

• Education: Bachelor’s degree in Software Engineering, Computer Science, Biomedical Engineering, or a related technical field is required; a Master’s degree or MBA is strongly preferred.
• Experience: 12+ years of experience in quality engineering or product development within the medical device industry, including 3-5 years in a formal management or leadership role.
• Certifications (Preferred): ASQ Certified Manager of Quality/Organizational Excellence (CMQ/OE), Certified Software Quality Engineer (CSQE), or Six Sigma Black Belt.

This position has an estimated base salary of $195,000 - $250,000, bonus, and equity. #LI-IB1; LI-Hybrid

As the Principal Risk Quality Engineer, you will own the product Risk Management process and will serve as the global subject expert (SME) for Product Safety and Risk Management. You will be the architect of the risk lifecycle, ensuring that our digital health solutions—including SaMD and AI/ML-enabled technologies—are designed with a "Safety-First" mindset.

Your core responsibility will be leading the end-to-end Risk Management process (ISO 14971), from initial Hazard Analysis through Post-Market Risk surveillance, ensuring that clinical risks are identified, mitigated, and verified before reaching a patient.  As a global SME of Risk Management, you will train and coach teams on Risk Management and work collaboratively with cross functional engineers and Quality team members.  

Key Responsibilities

Strategic Leadership

• Risk Governance: Act as the primary authority on global risk standards, including ISO 14971, IEC 62304 (Risk focus), and ISO/TR 24971.
• Safety Architecture: Define the framework for evaluating risk in AI/ML (algorithmic bias/drift), Cloud Infrastructure, and Cybersecurity (AAMI SW96/TIR57).
• Cybersecurity:  Partner with Cybersecurity team to evaluate and address cybersecurity related risks and ensure processes adhere to U.S. and international standards and guidance documents.  
• Risk Culture: Lead cross-functional "Safety-by-Design" workshops, ensuring engineering and product teams understand the clinical impact of technical failures.

Design Quality & Risk Management

• Advanced Risk Modeling: Lead and facilitate comprehensive risk activities, including Hazard Analysis, Fault Tree Analysis (FTA), and FMEAs (System, Design, and Software).
• Benefit-Risk Analysis: Partner with Clinical Affairs to author Benefit-Risk Assessments (BRA) for global regulatory submissions.
• V&V Alignment: Ensure that the Software Verification & Validation (V&V) strategy is directly driven by the Risk Management File (RMF), ensuring all mitigations are rigorously tested.

Execution & Compliance

• Risk Management File (RMF) Ownership: Drive the creation and maintenance of the RMF from concept through commercialization, ensuring a "living document" approach.
• Post-Market Risk Surveillance: Lead the review of field performance data and complaints to update risk assessments and trigger Corrective and Preventive Actions (CAPA) when necessary.
• Health Hazard Evaluations (HHEs): Lead necessary HHE activities related to quality and safety issues.    
• Audit Representation: Serve as the global SME, defending the technical integrity of the Risk Management process and files and technical safety justifications during FDA, Notified Body, and MDSAP inspections.

Cross-Functional Collaboration

• Clinical Collaboration: Bridge the gap between technical software failures and clinical harms by working closely with Medical Affairs.
• Regulatory Submissions: Provide critical risk-based evidence for FDA 510(k)/PMA and EU-MDR technical files.

Skills Needed

• Mastery of Risk Estimation, Evaluation, and Control methodologies.
• Strong critical thinking skills with the ability to visualize complex system-level failure modes.
• Ability to translate technical software bugs into potential clinical patient harms.

Educational Requirements & Work Experience 

• Bachelor’s degree in Biomedical Engineering, Systems Engineering, or a related technical field; Master’s degree strongly preferred.
• 10+ years of experience in Risk Management or Quality Engineering within the medical device industry.
• Certifications (Preferred): ASQ Certified Risk Management Professional, Six Sigma Black Belt, or ISO 14971 Lead Auditor.

This position has an estimated base salary of $185,000 - $240,000, bonus, and equity. #LI-IB1; LI-Hybrid

Role Overview 

We are seeking highly skilled, and motivated Director of Combination Product & Device Development, to lead the development, manufacturing, assembly and commercialization of high‑concentration biologic delivery systems, including, prefilled syringes, autoinjectors and other drug–device combination products.

The ideal candidate brings deep expertise in device design control, verification and validation, risk management, combination product regulations, and human factors engineering. This role requires hands‑on technical leadership and extensive experience with regulated devices and combination products (21 CFR 820, ISO 13485), as well as strong knowledge of global device standards (ISO, IEC 62366, ANSI/AAMI HE75) and FDA guidance. A successful track record supporting major regulatory submissions (BLA, MAA, IND/IMPD) and notified body assessments is essential.

Key Responsibilities 

Device Development

• Lead end‑to‑end development and commercialization of prefilled syringes, dual‑chamber cartridges, autoinjectors, and related combination product systems.
• Serve as a hands‑on technical leader and device SME across concept, feasibility, development, qualification, and launch phases.
• Define user needs and product requirements; lead prototyping, test method development, and design verification and validation (DV/V) activities.
• Drive design control documentation, risk assessments, usability studies, and human factors integration.
• Collaborate deeply with internal partners across CMC, drug product development, quality assurance, regulatory affairs, clinical development, supply chain, and commercial functions.
• Build and manage external relationships with CDMOs, device manufacturers, design firms, and suppliers to support development and lifecycle needs.
• Support lifecycle management of commercial combination products, including design history file (DHF) maintenance, change control, validation activities, complaint investigations, and post‑market surveillance.
• Evaluate technical decisions for cross‑functional impact and implement contingency plans as needed.
• Proactively identify and address manufacturing issues; coordinate technical solutions across internal and external teams.
• Lead creation of design control deliverables to ensure compliance with global device and combination product regulations.
• Oversee development of statistically sound verification protocols, reports, and design validation strategies.
• Lead or contribute to investigations of deviations, failures, complaints, and device‑related quality issues.

Design Controls & Human Factors

• Serve as the organizational expert in Human Factors Engineering, ensuring compliance with IEC 62366, ANSI/AAMI HE75, FDA guidance, and related industry standards.
• Integrate usability, human performance considerations, and safety risk mitigations into system requirements and development strategies.
• Ensure all human factors processes, deliverables, and standards are appropriately documented within the Design Control Quality System.
• Lead the cross‑functional design control sub‑team and drive cohesive integration across device design, analytical testing, packaging, manufacturing, clinical, supply chain, commercial, and regulatory functions.
• Manage and prioritize multiple concurrent projects, ensuring alignment to scope, timelines, budgets, and quality standards.

Regulatory Support

• Ensure compliance with global combination product and medical device regulations, including FDA and EU frameworks (e.g., EDDO, MDR).
• Author device‑related sections for regulatory submissions (BLA, MAA, IND/IMPD) and support notified body interactions.
• Represent the combination product function during regulatory audits and inspections.
• Lead proactive risk identification, mitigation planning, and escalation of critical issues.
• Demonstrate strong understanding of FDA’s Office of Combination Products (OCP), including primary mode of action (PMOA) requirements and combination product complaint expectations.

Qualifications 

• Master’s degree (or equivalent) in Mechanical Engineering, Biomedical Engineering, Chemical Engineering, or a related field.
• 15+ years of experience in biologic delivery device development with a proven record of supporting late‑stage development and commercial product launches.

• Experience with design controls, device risk management, medical devices, prefilled syringes, autoinjectors, and related scientific and technical concepts and techniques is required for this position.
• Deep knowledge of subcutaneous delivery systems, systems engineering principles, device materials, and manufacturing technologies; experience with biologics and packaging development preferred.
• Strong understanding of FDA and EU regulations for medical devices and combination products, including relevant quality systems and standards.
• Experience managing external partners, vendors, and contract manufacturers.
• Proven experience with cGMP process development, manufacturing controls, and process risk assessments.
• Excellent communication, leadership, and cross‑functional collaboration skills.
• Ability to thrive in a fast‑paced, agile environment; start‑up experience is highly desirable.

Position Location 

This is a fully remote role with up to 15-20% domestic and/or international travel.

The anticipated salary range for candidates for this role is $210,000 - $235,000. The final salary offered will depend on several factors, which may include, but not limited to, relevant years of experience, educational background, and geography. 

About Beneficial Deployments:

Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most.

About the Role:

We're looking for an Applied AI Engineer to join our Beneficial Deployments team, focused on maximizing the impact of Claude in the life sciences. Our goal is ambitious: accelerate scientific progress from R&D through translation by an order of magnitude. That means making Claude the go-to tool for the life sciences ecosystem from early discovery in academia to paradigm shifting biotech to reimaging pharma pipelines  — and building the technical infrastructure to back that up.

You'll work directly with flagship research partners like Howard Hughes Medical Institute and The Allen Institute, embedded in their scientific workflows. This isn't consulting from the outside — you'll be building alongside their engineers, prototyping agents that fit into real research pipelines, and developing the ecosystem-level tooling (MCP servers, benchmarks, reusable agent skills) that extends Claude's usefulness across the broader life sciences community. This role will be part of the founding Beneficial Deployments applied AI team focused on bringing more of life sciences closer to the frontier and be responsible for building with our partners. 

Responsibilities:

• Partner deeply with flagship life sciences research institutions — understand their scientific workflows end-to-end, build hands-on with their engineering teams, and help take projects from early exploration to production systems integrated into how they do science day-to-day.

• Develop reusable ecosystem infrastructure, like MCP servers for domain-specific data sources (genomics platforms, literature databases, experimental repositories), instruments, scientifically-grounded benchmarks, and agent skills that other institutions can adopt without starting from scratch.

• Identify what's actually hard about deploying AI in life sciences (heterogeneous data, auditability requirements, the prototype-to-trust gap) and feed those findings back to product, engineering, and research.

• Create technical content and documentation that lets partners self-serve, so what works for one institution can scale globally without the same level of hand-holding.

You Might Be a Good Fit If You Have:

• 4+ years as a Software Engineer, Forward Deployed Engineer, or technical founder — with production experience shipping systems that real users depend on.

• Deep research experience in life sciences, biomedical research, or scientific computing. Bonus if you've studied genomics, neuroscience, or drug discovery specifically and are comfortable getting deeply technical with academics.

• Experience building LLM-powered tools or applications: prompting, context engineering, agent architectures, evaluation frameworks.

• Builder credibility from shipping production code as a software engineer, forward-deployed engineer, or technical founder.

• A scrappy mentality–comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission.

What You Will Contribute To Altos

As part of our team, you will help to accelerate and optimize our progress in agentic AI methods for biological and clinical data curation and analysis.

In this role, you will be an integral part of our multidisciplinary teams building the computational platforms that will enable Altos to achieve its mission. You will collaborate with biomedical research experts as well as other machine learning scientists and engineers across the Institute of Computation to contribute to the Altos research and translation ecosystem, focusing on designing and building state-of-the-art agentic AI systems and workflows that tackle biological questions, accelerate clinical data analysis, and aid in the discovery of novel interventions for aging and disease.

The successful candidate will combine deep expertise in agentic AI methods with a strong foundation in bioinformatics and/or clinical R&D. You will work closely with domain experts to translate complex biological and clinical data challenges into intelligent, automated solutions. You will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Design and develop agentic AI workflows for biological and clinical data curation tasks
• Research and implement advanced context engineering techniques (RAG, agentic RAG, graph RAG) tailored to biomedical data
• Develop and optimize prompts and agent architectures for reliability, accuracy, and scientific rigor
• Build LLM-based tool-use systems and integrations relevant to bioinformatics and clinical R&D pipelines
• Collaborate with bioinformatics scientists, clinical researchers, and domain experts to identify automation opportunities and translate them into agentic solutions
• Evaluate and benchmark agentic systems, establishing rigorous metrics for performance and correctness in scientific contexts
• Stay current with the rapidly evolving landscape of agentic AI methods and contribute to internal best practices

Who You Are 

• Proven track record leveraging machine learning and AI to solve real-world problems
• Expertise in agentic AI methods development, including prompt optimization, LLM-based tool use, context engineering (RAG, agentic RAG, graph RAG), and agent evaluation
• Experience writing production-quality code with agentic frameworks (e.g., LangGraph, Pydantic-AI, DSPy, or similar)
• Deep familiarity with bioinformatics and/or clinical R&D, with the ability to engage meaningfully with domain experts on biological and clinical questions
• Proficiency with AI-assisted development tools (e.g., Claude Code, Cursor) to iterate rapidly
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focused on professional growth
• Able to advise others across the wider function / company on cutting edge agentic AI practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, machine learning, and medicine
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities

Minimum Qualifications

• PhD in Computer Science, Machine Learning, Bioinformatics, or a related field
• Demonstrated experience developing agentic AI systems, including LLM-based tool use, prompt engineering, and context engineering techniques
• Strong foundation in machine learning principles and their application to real-world problems
• Strong background in bioinformatics, computational biology, or clinical R&D
• Familiarity with MCP server development and agent skill creation
• Very strong programming skills in Python, with experience writing production-quality, well-documented code
• Strong track record of published peer-reviewed research in AI/ML and/or computational biology

Preferred Qualifications

• Experience with AWS services (S3, Bedrock, Lambda) in the context of AI/ML workflows
• Experience with clinical trial data, regulatory data curation, or biomedical ontologies (e.g., CDISC, SNOMED, MedDRA)
• Track record working with NGS data (e.g., RNA-seq, ATAC-seq, DNA methylation) or other biological data modalities
• Experience designing evaluation frameworks and benchmarks for agentic AI systems
• Familiarity with knowledge graph construction and graph-based retrieval methods

The salary range for Redwood City:

• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego:

• Senior Scientist I, Machine Learning: $239,500 - $307,000

Exact compensation may vary based on skills, experience, and location.

#LI-NN1

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

What You Will Contribute To Altos

Altos Labs is building a world-class AI ecosystem to solve the most complex problems in human biology. You will directly design and build high-performance, scalable solutions that unify high-dimensional biomedical imaging with molecular and language data.

By implementing large-scale multimodal data fusion, you will move beyond simple image analysis to create predictive models that map across biological domains. You will be hands-on with the data and the code, collaborating with our engineering team to ensure these models are scalable, efficiently trainable on distributed cloud infrastructure, and accessible to our global research community.

Responsibilities

• Model Development: Design, code, and train large-scale foundation models (e.g., Vision Transformers, Multimodal LLMs) that can embed spatial data and integrate multiple modalities.
• Hands-on Data Fusion: Implement innovative cross-domain mapping and fusion strategies to synchronize heterogeneous biological datasets.
• Scaling & Training: Build and manage high-performance ML pipelines capable of processing petabyte-scale image repositories and multi-omics streams in a cloud environment.
• Technical Collaboration: Work directly in the trenches with experimental scientists and software engineers to translate biological complexity into performant code and reliable distributed systems.

Who You Are

We are looking for a technical specialist who thrives on solving "unsolvable" problems through code and rigorous experimentation. We are open to candidates at the Scientist I, Scientist II, or Senior Scientist level based on technical expertise.

Minimum Qualifications

• Education: PhD in Computer Science, AI/ML, Biomedical Engineering, or a related quantitative field.
• Hands-on CV Expertise: Deep experience building and deploying modern Computer Vision architectures (Vision Transformers, U-Nets, Self-Supervised Learning).
• Distributed Training: Proven experience training and fine-tuning large models at scale using frameworks like PyTorch Distributed, DeepSpeed, or Jax.
• Programming Mastery: Expert-level Python skills, with a focus on building production-ready machine learning code and large-scale data management systems.
• Scientific Contributions: A track record of technical contributions via high-impact publications (CVPR, ICCV, NeurIPS, etc.) or significant contributions to open-source ML frameworks.

Preferred Qualifications

• Direct experience with Multimodal Fusion (e.g., aligning image embeddings with transcriptomic or proteomic data).
• Proficiency with cloud-native AI tools (AWS/GCP, Kubernetes, Docker) and building automated MLOps workflows.
• Experience handling the unique noise and sparsity of biological data.

The salary range for Redwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

#LI-NN1

Exact compensation may vary based on skills, experience, and location.

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

About

Edison Scientific builds and commercializes AI agents for science. Scientific discovery moves too slowly, and autonomous AI agents are how we intend to fix that. We're assembling a team of top researchers and engineers across AI and biology to build an AI scientist.

Role

We're looking for an Applied AI Engineer to join the team responsible for building Edison's most powerful AI agents. Half of the public agents on our platform, including Kosmos, our flagship product, came directly out of this team.

You'll own the development and maintenance of production agents, prototype new capabilities with our internal science and engineering teams, and shape how our platform evolves. You'll spend some time with customers to understand real workflows and validate what you're building, but your primary focus is on the agents themselves – making them more capable, more reliable, and more useful across the life sciences.

Responsibilities

• Architect, implement, and maintain the AI agents that power Edison's platform, from prototype through production.
• Work with our internal science and engineering teams to explore new agent architectures, prompting strategies, tool integrations, and evaluation frameworks.
• Develop reusable infrastructure – agent skills, tool-use pipelines, benchmarks – that improves every agent on the platform.
• Spend time with R&D partners (~30%) to understand their workflows, test what you've built in real environments, and bring insights back to the team.
• Translate field insights and internal research into product direction – help the team prioritize what to build next.

Qualifications

• 3+ years of professional software engineering experience, with production experience shipping systems that real users depend on.
• Experience building LLM-powered tools or applications: prompting, context engineering, agent architectures, evaluation frameworks.
• Strong engineering foundation in Computer Science, Software Engineering, Mathematics, Physics, Data Science, or a related technical field.
• Proficiency in Python and/or TypeScript, with comfort picking up new tools and frameworks quickly.
• Able to work across engineering, science, and product teams.
• Comfortable building from scratch, driving clarity in ambiguous situations, and wearing multiple hats.

Bonus points for:

• Experience in life sciences, biomedical research, scientific computing, or technical R&D workflows.
• Experience building agent systems, tool-use pipelines, or evaluation/benchmarking frameworks for AI applications.
• Contributions to open-source scientific or AI tooling.

Salary

$160,000 - $280,000  •  Offers equity

Why join us?

• Competitive salary and equity
• Full healthcare coverage — we pay 100% of premiums for you and your dependents
• Support for growing families, including a yearly new parent stipend and fertility coverage through Carrot
• 401(k) company matching
• $300 health and wellness benefit
• Lunch is on us every day you're in the office, and dinner is on us when you're working late
• Regular team offsites and company events
• A fast-moving, mission-driven culture where smart people do their best work and actually enjoy doing it

About the Job

We are hiring a Director, Scientific Affairs who brings both scientific depth and a genuine passion for connecting people, evidence, and ideas. In this role, you'll be at the center of our clinical and commercial efforts; helping translate complex science into clear, compelling stories that move the field forward.

You'll partner closely with teams across Ossium to shape medical and scientific strategy, supporting the commercial launch of our novel cryopreserved bone marrow, and leading medical education and data communication work that actually changes how clinicians think about treating patients. Whether you're collaborating with individual clinical sites on evidence-generation projects or working alongside the commercial team to bring our flagship product to patients in need, you'll be the bridge between science and impact.

This is an excellent role for someone who thrives at the intersection of rigor and relationship-building; the ideal candidate is someone who can walk into a room of scientists, surgeons, or sales leads and speak everyone's language. 

This role reports directly to the Chief Medical Officer.

Required Qualifications

• MD/PhD in a life science/biomedical discipline with strong clinical experience
• 5+ years of industry experience 
• Proven ability to collaborate, partner, and influence across multiple functions and levels of leadership
• Demonstrated experience with manuscript and abstract writing and post hoc data analyses
• Experience working with MSLs and providing medical/scientific support to commercial teams
• Proven agility and adaptability in a fast-paced, results-driven startup environment
• Excellent written, verbal, and presentation communication skills
• Understanding of biostatistical concepts to analyze clinical trial data
• Comfortable with travel from 15% - 30%
• This position is based in our San Francisco office; we maintain a hybrid schedule of Monday - Thursday in the office, with Friday as a remote work day
• Qualified candidates must be legally authorized to be employed in the United States; Ossium is unable to provide sponsorship for employment visa status (eg, H-1B or TN status) for this position, either now or in the future

Preferred Qualifications

• Scientific or clinical expertise in hematologic malignancies, hematopoietic cell transplantation (HCT), or cell therapy
• Experience supporting product launch 
• Background in rare disease or a specialized therapeutic indication (e.g., bone marrow transplantation)
• Experience in clinical development or protocol support

Key Responsibilities

• Drive scientific communications internally and externally, including data dissemination, educational initiatives, and guideline/value-proposition development
• Assist with strategic publication planning and writing/preparing manuscripts, abstracts, and presentations
• Collaborate closely with Medical Science Liaisons (MSLs) to generate, synthesize, and communicate scientific insights from field interactions
• Assist with initiating and maintaining relationships with transplant MDs and PIs
• Lead evidence-generation initiatives (clinical, secondary analyses, real-world evidence) to enhance understanding of therapeutic benefit and value
• Serve as medical reviewer on the Promotional Review Committee and ensure scientific accuracy and compliance of promotional materials
• Support congress planning and KOL engagement efforts in partnership with the Medical Science Liaison team
• Provide strategic medical and scientific input into brand strategies, supporting product launches and ongoing commercialization activities
• Provide medical guidance to clinical operations teams and support cross-functional collaboration with Commercial, Market Access, Regulatory, and Clinical Development
• Generate and maintain proactive educational content to support internal training and external stakeholder engagement
• Travel as needed  to scientific meetings, clinical sites, or investigator interactions

In your first six months some projects you’ll work on include:

• Supporting authorship and submission of manuscripts and abstracts to major scientific meetings (e.g., ASH, TANDEM)
• Partnering with field and commercial teams to deliver clinical and scientific support for product-launch activities for HPC, Marrow
• Establishing relationships with individual sites and PIs to initiate evidence generation projects

This position has a salary range of $200,000 - $275,000 annually. Ossium Health takes a market-based approach to pay. The successful candidate’s starting salary will be determined based on, but not limited to, job-related skills, experience, qualifications, and market conditions. This range may be modified in the future.

We offer a full slate of employee benefits including:

• Stock options
• 401(k) matching
• Medical, dental and vision coverage
• Generous paid time off + 11 company holidays
• Employer paid life insurance and long-term disability
• Gym membership/recreational sports reimbursements

About the role

We’re looking for a Machine Learning Engineer (Life Sciences) to help build our platform for training, evaluating, and deploying interpretable frontier AI systems, with an emphasis on scientific and biological foundation models(e.g., genomic foundation models, protein language models, vision models for digital pathology).

Where you might contribute:

• Forward deployed research – lead scientific research with our partners to interpret advanced biological foundation models (genomic foundation models, ViTs, PLMs) to uncover what they’ve learned.
• Project delivery and implementation – own research delivery on high-stakes projects with customers and do whatever it takes to make delivery successful, including: problem and hypothesis definition, data sourcing, tool building, iteration, and implementation. Translate research into tools for real-world applications in precision medicine, digital pathology, drug discovery, and more.

Key responsibilities:

• Productionize interpretability research into maintainable tools, APIs, and workflows that work on real models and real scientific data.
• Optimize pipelines and infrastructure for frontier model interpretability, training, and inference.
• Prototype techniques to visualize and manipulate internal model structures.
• Integrate new machine learning workflows and pipelines into our product and deploy to customers.
• Ensure system reliability, reproducibility, and performance

What you’ll bring

Required experience

• 5+ years of experience in ML infra, research engineering, or systems programming.
• Comfort working across research and engineering boundaries.
• Expertise in Python, PyTorch or Jax, and distributed systems.
• Experience deploying and maintaining ML systems at scale.
• You care about understanding how models work internally and using that to make them more reliable and useful in the real world

Preferred qualifications

• Experience with biological / life sciences ML (computational biology, bioinformatics, digital pathology, protein/genomics, multimodal biomedical data).
• Open-source ML infrastructure contributions.
• Startup or frontier-lab experience in fast-moving teams

Our values

Goodfire is looking for individuals who embody our values and share our deep commitment to making interpretability accessible. We are building a team first and foremost.

Put mission and team first

All we do is in service of our mission. We trust each other, deeply care about the success of the organization, and choose to put our team above ourselves.

Improve constantly

We are constantly looking to improve every piece of the business. We proactively critique ourselves and others in a kind and thoughtful way that translates to practical improvements in the organization. We are pragmatic and consistently implement the obvious fixes that work.

Take ownership and initiative

There are no bystanders here. We proactively identify problems and take full responsibility over getting a strong result. We are self-driven, own our mistakes, and feel deep responsibility over what we’re building.

Action today

We have a small amount of time to do something incredibly hard and meaningful. The pace and intensity of the organization is high. If we can take action today or tomorrow, we will choose to do it today.

Where we work

We are hiring for this position in our San Francisco HQ. We are in person 5 days a week, with one company-wide remote week per month.

What we offer

This role offers market competitive salary, equity, and competitive benefits.

The expected salary range for this position is $200,000 - $400,000 USD (depending on level and scope).

Most importantly, you'll have the opportunity to join a vital mission at an important point in its trajectory — we are developing groundbreaking technology with a world-class team on the critical path to ensuring a safe and beneficial future for humanity. If you want to do your life’s work with us, even if you believe you do not meet every single requirement, apply now.

We are looking for a Health Sensing Hardware Engineer to join our hardware team working on future wearables and accessory devices reporting directly to the Director, Hardware Sensing Technologies.  This opportunity will be hybrid out of our San Francisco or San Diego office.

What you will do: 

• Develop and validate physiological sensing systems for acquiring and analyzing physiological signals in wearable health and wellness products
• Define hardware and software technical specifications and implement test and calibration protocols both internally and at manufacturer sites
• Ensure that the physiological sensors integrated in our products meet their specifications from prototype to mass production
• Build and validate hardware architectures optimized for low-noise, high-resolution time-series signal collection
• Plan and execute benchtop and on-body testing to evaluate system performance across various user populations
• Support validation and compliance efforts in collaboration with regulatory, research, and clinical teams
• Work cross-functionally to ensure end-to-end system performance and signal integrity
• Conduct rigorous testing and troubleshooting to ensure sensor performance across varying environmental and use-case conditions
• Collaborate closely with mechanical and electrical engineers to integrate sensors within constrained form factors and flexible layouts
• Partner with firmware and software teams to enable and refine features built on physiological data
• Work directly with sensor vendors to evaluate new components, optimize performance, and address integration challenges
• Travel occasionally to Finland and to global manufacturing or development sites as required (15%–20%) 

Requirements:

We would love to have you on our team, if you have:

Technical Expertise 

• Strong electrical engineering background and experience with the design and testing of low-noise analog or mixed-signal systems
• Strong understanding of time-series physiological signal acquisition, including best practices for minimizing noise and motion artifacts
• Familiarity with algorithmic methods for time-series signal modeling and calculating physiological metrics
• Simulation and modeling experience using tools like ANSYS, CST, or COMSOL
• Skilled in embedded software and data acquisition tools such as C/C++, Python, or similar
• Experience with data analysis and signal processing tools such as Python, MATLAB, or JMP

Problem Solving and Analytical Thinking

• Strong experimental and analytical skills with a methodical approach to isolating and debugging complex issues across hardware and algorithm domains
• Ability to work independently through ambiguity and rapidly iterate on early-stage concepts
• Driven by data and eager to understand root causes behind performance issues

Communication and Collaboration

• Effective communicator across disciplines, with the ability to clearly convey technical insights both in written and verbal form to technical and non-technical audiences
• Experience working in cross-functional teams spanning hardware, firmware, product, and research
• Contributed to project documentation, planning, and alignment with stakeholders

Educational Background

• Bachelor’s degree in electrical engineering, mechanical engineering, biomedical engineering, physics,or related field with 7+ years of relevant industry experience
• Master’s degree with 5+ years, or PhD with 2+ years of relevant industry experience

Prototyping and Testing

• Hands-on experience building and characterizing early-stage hardware systems
• Proficiency using various lab instrumentation tools such as digital multimeters, oscilloscopes, signal generators, spectrum analyzers, physiological simulators, power analyzers, and environmental chambers

Bonus Points:

• Experience developing or integrating physiological sensing systems into wearable or health-oriented products
• Track record of supporting high volume products from early prototyping through manufacturing and launch
• Knowledge of regulatory or safety standards for health-related technologies
• Prior work in validation studies or performance benchmarking across diverse populations

Benefits 

At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health and add to our benefits!

What we offer:

• Competitive salary and equity packages
• Health, dental, vision insurance, and mental health resources
• An Oura Ring of your own + employee discounts for friends & family
• Fertility benefits through Carrot Pro
• Flexible working hours and remote working arrangements
• $750 Learning & Development credit
• 20 days of PTO + 13 paid holidays + 8 days of flexible wellness time off
• 5 days paid sick leave, 5 days bereavement leave, 12 weeks paid parental leave
• Amazing culture of collaborative and passionate coworkers

Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates’ pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

• Region 1 Range (SF): $217,000 - $267,950
• Region 2 Range (SD): $197,000 - $243,800

A recruiter can determine your zones/tiers based on your US location.

To all recruitment agencies: Oura does not accept agency resumes. Please do not forward resumes to our jobs alias, Oura employees or any other organization location. Oura is not responsible for any fees related to unsolicited resumes.

Oura is proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. Individuals seeking employment at Oura are considered without regards to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by federal, state, or local laws. We will not tolerate discrimination or harassment based on any of these characteristics.

Role

The AI Team at Vivodyne tackles some of the hardest and most interesting challenges in science and engineering. With access to extraordinarily feature-rich and massive-scale Vivodyne human tissue imagery, we are advancing the frontiers of artificial intelligence and its applications in biology. We are building a portfolio of AI technologies to automate the discovery, development, and de-risking of novel therapies using our unique technology platform, including single-cell 3D phenomics/machine vision, multimodal (multi-omic) translation, and reinforcement learning for robotic planning & study design, among others.

As an AI Senior Scientist, you will leverage your deep expertise in developing large-scale models (including Transformer, Diffusion, and hybrid architectures) and Generative AI solutions to help turn our state-of-the-art imaging and multi-omics datasets into groundbreaking scientific insights. You will collaborate closely with biologists, engineers, and AI specialists to deliver robust, production-ready algorithms and models that power Vivodyne’s high-impact discoveries.

This role will be based on-site at our offices in Brisbane, California

Responsibilities

• Scientific Innovation — Work closely with internal and external stakeholders to understand their scientific objectives and innovate new approaches that utilize Vivodyne’s massive-scale imaging and multi-omics datasets.

• Model Development — Lead hands-on development of cutting-edge machine learning models (Transformers, Diffusion, hybrid architectures, etc.) with a focus on image processing, image enhancement, and Phenomap embeddings.

• Data Pipeline Optimization — Build and deploy pipelines capable of scaling to petabyte-scale data, ensuring robust MLOps practices on AWS or equivalent cloud platforms.

• Multimodal Integration — Explore and develop novel methods to incorporate multi-omics data into imaging-based Phenomaps, advancing the state of the art in multimodal phenotypic analysis.

• Collaboration & Communication — Partner with tissue engineers, microfluidics experts, and robotics engineers to refine data collection strategies, provide feedback on imaging system performance, and identify opportunities for improved AI-driven solutions.

• Scientific Rigor & Leadership — Uphold scientific excellence through peer reviews, proper documentation, and clear communication. Drive a culture of continuous improvement, best practices, and adherence to rigorous research methodologies.

• Scalability & Efficiency — Emphasize modularity, composability, and performance efficiency in designing and implementing high-throughput compute and analytics pipelines.

• Domain & Technical Growth — Remain current with the latest research trends in Generative AI, biomedical imaging, cloud computing, and data-intensive training. Proactively share knowledge and mentor teammates to foster overall organizational expertise.

Requirements and Expectations

• Scientific Excellence — Stay current with AI/ML research, especially in Generative AI, Transformers, Diffusion models, and multi-modal architectures. Apply rigorous, data-driven methods for sound outcomes.
• Hands-On Leadership — Set high standards for model development and code quality, mentoring team members and fostering innovation.
• Accountability — Own model and infrastructure development from concept to deployment, delivering reliable, scalable solutions aligned with Vivodyne’s mission.
• Problem Solving & Adaptability — Develop creative solutions to novel research challenges, thriving in a fast-paced, dynamic startup environment.
• Collaboration & Communication — Work cross-functionally to align AI strategies with business goals, ensuring clear communication and consensus-building.
• Delivering Results — Prioritize impactful research, using project management best practices to track progress, mitigate risks, and meet deadlines.
• Architecture & Coding — Design scalable, cost-effective systems and produce clean, well-documented code with continuous testing and governance compliance.
• Resource Optimization — Apply financial discipline to maximize the efficiency of compute, storage, and third-party services.
• Team & Thought Leadership — Foster an inclusive environment, mentoring future leaders and representing Vivodyne in AI research and industry discussions.

Qualifications

• Education & Experience

• PhD in Computer Science, Applied Mathematics, or a related field, or equivalent practical experience.
• Proven expertise developing and deploying advanced ML architectures (Transformers, Diffusion, multi-modal models) in Generative AI settings.
• Demonstrated history of success with image processing and large-scale model training.

• Technical Skills

• Strong knowledge of AWS or another major cloud provider for MLOps, big data processing, and scalable computing.
• Experience building models for petabyte-scale datasets and understanding the associated architectural and operational complexities.

• Domain Expertise (Preferred)

• Familiarity with biological or biomedical imaging; advanced knowledge in multi-modal Phenomaps, especially integrating imagery with multi-omics data, is a major plus.

• Additional Desired Skills

• Prior experience with HPC, GPU clusters, or distributed computing frameworks.
• Comfortable with container orchestration and open-source data engineering/ML frameworks.

• Soft Skills & Leadership

• Strong written and oral communication skills, with a proven ability to present complex technical topics to non-experts.
• Demonstrated ability to thrive in ambiguous environments, driving clarity and direction with minimal supervision.

Vivodyne, Inc. is an equal opportunity employer. Vivodyne complies with all laws respecting equal employment opportunity and does not discriminate against applicants with regard to any protected characteristic as defined by federal, state, and local law.