About this opportunity:

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

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

What you’ll do:

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

Must haves:

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

Nice to haves:

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

Benefits and additional information:

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

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

Applicants have rights under Federal Employment Laws.  

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

#LI-REMOTE

Role

The Software & Data Science team at Vivodyne tackles some of the hardest problems at the intersection of human biology, large-scale data, and machine learning using uniquely rich imaging and multi-omics datasets from lab-grown human tissues.

We are expanding our capabilities to generate high-throughput -omics data across automated human tissue models, with a primary focus on single-cell and bulk transcriptomics, secretomics, and proteomics. We're looking for a Bioinformatician who can develop new analytical methods and build robust infrastructure to support them at scale.

You will define how we process, store, integrate, and interpret biological datasets, making foundational decisions that shape the long-term utility of our data for internal research, AI/ML model development, and external partners. This means owning both the science (what question does this analysis answer, and how defensible is the conclusion?) and the engineering (does this pipeline run reliably at scale, and can someone else extend it?).

This is a high-impact, cross-functional role. You'll sit within the Software & Data Science organization and collaborate daily with experimental biologists, AI/ML researchers, software engineers, and client-facing teams.

This is a full-time, onsite role in San Francisco.

Responsibilities

Develop and Own Analytical Methods

• Design, implement, and critically evaluate computational approaches for scRNA-seq, bulk RNA-seq, secretomics, and proteomics data including QC, normalization, batch correction, dimensionality reduction, clustering, differential expression, trajectory analysis, and multi-dataset integration.
• Go beyond applying standard tools: develop or adapt methods for perturbation modeling, causal inference, network reconstruction, ligand-receptor inference, and multi-omics integration as the science demands.
• Select and standardize tooling based on rigorous benchmarking, not convention. Challenge default choices when the data or use-case warrants it.

Build Scalable, Production-Grade Pipelines

• Architect end-to-end analysis workflows in Python and/or R using modern workflow orchestration (Nextflow, Snakemake, or equivalent) that are reproducible, version-controlled, and designed to run at the scale of tens to hundreds of thousands of samples.
• Partner with software and data engineers to productionize pipelines, ensure robust data ingestion and storage, and contribute to decisions on biological data architecture (storage formats, schema design, long-term data usability).
• Write well-documented, testable code that other engineers and scientists can run, review, and extend.

Drive Biological Insight and Interpretation

• Own dataset analysis to answer biological and client-driven questions with rigor. Ground conclusions in the limits of the data and clearly communicate what can and cannot be concluded with confidence.
• Partner with experimental biologists to frame the most relevant biological questions, design analyses, and recommend experiments and data-generation strategies to fill key gaps.
• Produce publication-quality figures, internal reports, and partner-facing deliverables that are decision-useful.

Shape Data Strategy

• Help define benchmarking strategies for internal tissue model development.
• Proactively identify opportunities to leverage internal and public datasets to accelerate scientific progress.
• Contribute to decisions around data standards, comparability, and the integration of omics features into downstream ML models and AI workflows.

Communicate Across Functions

• Translate complex multi-omic analyses into clear insights for biologists, AI/ML researchers, software engineers, and non-technical stakeholders.
• Tailor depth and framing to the audience while maintaining scientific rigor.

Requirements and Expectations

Technical Expertise

• Ph.D. in Computational Biology, Bioinformatics, Genomics, Systems Biology, Biostatistics, or a related quantitative field with deep focus on transcriptomics and/or proteomics.
• 2–5 years of post-PhD experience; some industry experience strongly preferred.
• Strong, hands-on proficiency in Python for bioinformatics (Scanpy and the broader scverse ecosystem in particular) with the judgment to know when existing tools are insufficient and the skill to build alternatives. Familiarity with R-based workflows (Seurat, Bioconductor, Monocle) is valued as evidence of breadth, but Python is the production language.
• Deep experience with scRNA-seq datasets and workflows, including QC, batch correction, clustering, differential expression, annotation, and integration across experiments.
• Experience with proteomics or secretomics analysis (Olink or similar high-dimensional panels), including normalization and cross-modality integration with transcriptomic profiles.
• Comfort in a Unix/Linux environment with standard dev tools (git, containers, CI/CD); experience with cloud environments (AWS) and workflow managers is a strong plus.
• Familiarity with data infrastructure for large-scale biological data (e.g., AnnData/H5AD, TileDB-SOMA, or similar) is a plus.

Problem Solving & Ownership

• Ability to independently structure and execute complex analytical projects from ambiguous initial questions to concrete, reviewable outputs.
• Strong biological intuition for distinguishing meaningful signal from artifact and the discipline to validate before interpreting.
• Comfortable navigating ambiguity in a fast-moving startup; can prioritize, make trade-offs, and hit agreed timelines.

Collaboration & Communication

• Excellent written and verbal communication; able to explain computational methods and biological implications to biologists, engineers, and non-technical stakeholders.
• Proven ability to collaborate across disciplines.

Innovation & Leadership

• Track record of taking omics analyses from raw data to figures/tables suitable for publications, reports, or decision meetings.
• Demonstrated ability to manage multiple analyses in parallel and ship work on predictable timelines.
• History of method development or meaningful adaptation of existing methods to novel data types or experimental designs.

Preferred Qualifications

• Experience with multi-modal data integration (e.g., combining imaging, transcriptomics, and proteomics features).
• Background in drug discovery, toxicology, or translational research where multi-omic data inform therapeutic decisions.
• Experience with representation learning or ML for biological data (embeddings for cells, genes, or proteins), especially in collaboration with ML specialists.
• Familiarity with organoids, primary tissues, or organ-on-chip systems.

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.

About this opportunity:

At Freenome, we are seeking a Senior Manager, Product Marketing - Blood Testing Portfolio to help grow the Freenome Marketing team. In this role, you will be instrumental in helping us launch our first products and driving adoption in the clinic. This position is responsible for architecting and executing marketing strategies that resonate across a complex healthcare ecosystem, inspiring action among providers and the patients they serve. The work centers on championing our pipeline of blood-based screening tests—including our lung cancer screening solution and future indications—ensuring our customers are empowered and informed by the next generation of early detection technology. This role is a vital pillar in Freenome’s mission to redefine the patient-provider experience and fundamentally shift the landscape of cancer through the power of multi-cancer screening.

The role reports to the Director, Product Marketing. This role will be a Remote role.

What you’ll do:

• You’ll be the Marketing lead for Freenome’s portfolio of cancer screening blood tests, developing and leading marketing strategies that ensure our tests are effectively communicated and resonate with providers and patients.
• Leverage voice of customer to develop and optimize the core value proposition and messaging for Freenome’s blood tests and ensure messaging, creative and tactics are maximized for impact.
• Collaborate cross-functionally with team members, including our our Product team on defining the patient experience for pipeline and in-market tests, and our sales teams as they engage directly with customers.
• Develop high-impact sales enablement resources to prepare field teams for upcoming product introductions.
• Drive customer insights through KOLs and advisory board meetings.
• Monitor the landscape of cancer screening blood test competitors and industry trends to ensure Freenome’s positioning remains differentiated in the space.
• Manage external creative and digital agencies to deliver compelling, differentiated, and on-brand marketing campaigns.
• Analyze market trends and campaign performance data to refine marketing strategies and drive future product growth.
  

Must haves:

• 7+ years of relevant experience and Bachelor’s degree in an analytical, technical, or scientific field; MBA strongly preferred.
• Experience marketing to providers and patients, ideally with a focus on primary care, preventative health and/or oncology.
• Experience marketing regulated or centralized laboratory-developed products and leveraging Med-Legal-Regulatory review process.
• Deep understanding of diagnostics and healthcare technology markets.
• Exceptional storyteller and communicator capable of explaining complex data science, machine learning, and clinical concepts in simple terms.
• Strong cross-functional leadership skills with proven experience managing complex projects through influence.
• An entrepreneurial mindset; comfortable with ambiguity, takes initiative, and possesses strong problem-solving skills.
• Experience building marketing collateral from scratch with little to no existing materials.
  

Nice to haves:

• Experience in marketing cancer screening, primary care, or preventive health products.
• Experience with CRM and digital marketing tools to enhance customer engagement.
  

Benefits and additional information:

The US target range of our base salary for new hires is $161,925 - $232,575. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

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

Applicants have rights under Federal Employment Laws.  

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

#LI-Remote

Associate Director, Quantitative Pharmacology and Pharmacometrics

Nurix Therapeutics is a biopharmaceutical company focused on the discovery, development and commercialization of small molecule therapies designed to modulate cellular protein levels as a novel treatment approach for cancer and immune disorders. Leveraging Nurix’s extensive expertise in E3 ligases together with its proprietary DNA-encoded libraries, Nurix has built DELigase, an integrated discovery platform to identify and advance novel drug candidates targeting E3 ligases, a broad class of enzymes that can modulate proteins within the cell. Nurix’s drug discovery approach is to either harness or inhibit the natural function of E3 ligases within the ubiquitin proteasome system to selectively decrease or increase cellular protein levels. 

Nurix’s wholly owned pipeline comprises targeted protein degraders of Bruton’s tyrosine kinase, a B-cell signaling protein, and inhibitors of Casitas B-lineage lymphoma proto-oncogene-B, an E3 ligase that regulates T cell activation.

Position

The Associate Director in the Clinical Pharmacology group will contribute to pharmacometric efforts across early and late-stage programs. As an early member of the Clinical Pharmacology group, you will have an opportunity to influence the direction of the clinical pharmacology group at Nurix. The successful applicant shall be proficient in developing and executing PK/PD modeling and simulation activities, such as but not limited to population PK/PD modeling, physiologically-based PK (PBPK) modeling and quantitative systems pharmacology (QSP) modeling. This includes data analysis and interpretation and presentation of findings to optimize doses, dosage regimens and study designs. The candidate will also author and review clinical pharmacology documents for submission and/or response to regulatory agencies. The candidate will be influential across multiple functions including individual contributors, development program teams, and the executive team.

Responsibilities

• Utilize quantitative approaches to impact model-informed drug discovery and development in areas such as human dose projections, dose regimen identification and optimization
• Lead and conduct pharmacometric workstreams such as but not limited to noncompartmental analyses, exposure-response analyses, population PK/PD modeling, PBPK modeling and QSP modeling, and running model-based simulations
• Conduct exploratory modeling activities to support decision-making and clinical strategy
• Collaborate across functions within the company and oversee contract vendors to advance pharmacometric efforts and activities
• Oversee and contribute to clinical pharmacology sections of clinical study protocols, SAPs, CSRs, stand-alone PK/PD reports, Clinical development plans
• Author and review clinical pharmacology documents for submission and/or response to regulatory agencies
• Actively identify state-of-the-art quantitative approaches in the field for potential applications to projects, including the use of artificial intelligence/machine learning (AI/ML) techniques

Qualifications

• PharmD or PhD or MS in a field related to Pharmacometrics with 8+ years of industry or similar experience in Pharmacometrics, Clinical Pharmacology or Quantitative Systems Pharmacology
• Extensive hands-on experience in using modeling and simulation techniques in pharmaceutical development, such as population PK/PD modeling, PBPK modeling or QSP modeling  
• Exceptional oral and written communication skills and excellent problem-solving skills
• Previous experience in authoring and reviewing clinical pharmacology documents for submission and/or response to regulatory agencies
• Demonstrated past performance of functioning efficiently in a dynamic, cooperative, team-oriented environment showcasing emotional intelligence (respect and empathy)
• High proficiency in using common software and data analysis packages (e.g., R, WinNonlin, Simcyp, GastroPlus, Monolix, NONMEM)
• Nurix is headquartered in Brisbane, California. This is an onsite position.

Salary Range:  208K– 240K plus bonus & equity.

Location:  Brisbane, CA – Onsite

Nurix Therapeutics, Inc. is committed to protecting and respecting your privacy and personal information, including information collected by Nurix when you apply for a job with Nurix or in the course of your employment with Nurix.  By applying for a position at Nurix, you agree to our collection and use of personal information as described in our Privacy Policy (https://www.nurixtx.com/privacy-policy/). 

PsiQuantum’s mission is to build the first useful quantum computers—machines capable of delivering the breakthroughs the field has long promised. Since our founding in 2016, our singular focus has been to build and deploy million-qubit, fault-tolerant quantum systems. 

Quantum computers harness the laws of quantum mechanics to solve problems that even the most advanced supercomputers or AI systems will never reach. Their impact will span energy, pharmaceuticals, finance, agriculture, transportation, materials, and other foundational industries. 

Our architecture and approach is based on silicon photonics. By leveraging the advanced semiconductor manufacturing industry—including partners like GlobalFoundries—we use the same high-volume processes that already produce billions of chips for telecom and consumer electronics. Photonics offers natural advantages for scale: photons don’t feel heat, are immune to electromagnetic interference, and integrate with existing cryogenic cooling and standard fiber-optic infrastructure. 

In 2024, PsiQuantum announced government-funded projects to support the build-out of our first utility-scale quantum computers in Brisbane, Australia, and Chicago, Illinois. These initiatives reflect a growing recognition that quantum computing will be strategically and economically defining—and that now is the time to scale. 

PsiQuantum also develops the algorithms and software needed to make these systems commercially valuable. Our application, software, and industry teams work directly with leading Fortune 500 companies—including Lockheed Martin, Mercedes-Benz, Boehringer Ingelheim, and Mitsubishi Chemical—to prepare quantum solutions for real-world impact. 

Quantum computing is not an extension of classical computing. It represents a fundamental shift—and a path to mastering challenges that cannot be solved any other way. The potential is enormous, and we have a clear path to make it real. 

Come join us. 

Job Summary:

Are you passionate about advancing quantum materials theory and computational modeling? As a Quantum Materials Theorist, you will join an interdisciplinary team at the forefront of computational physics, materials science, machine learning, and quantum technologies. This role offers the opportunity to develop and refine theoretical and computational approaches for understanding and predicting material properties, contributing to next-generation technologies.

You will bring expertise in electronic structure theory, many-body physics, and computational methods to explore complex quantum materials and emergent phenomena. Your work will involve integrating conventional and emerging computational approaches, incorporating insights from machine learning, high-performance computing (HPC), and quantum computing to drive innovation in materials discovery and design.

This position provides the opportunity to engage in high-impact, collaborative research, working alongside specialists in quantum algorithms, materials informatics, computational physics, chemistry, and condensed matter modeling. If you thrive in an intellectually stimulating environment and enjoy tackling fundamental and computational challenges in quantum materials science, we encourage you to apply.

This position requires a PhD in computational physics (or a closely related field), preferably with postdoctoral research experience (although postdoc experience is not mandatory). We are looking for a curious, creative, and interdisciplinary thinker with a comprehensive understanding of various computational physics, chemistry, and machine learning methodologies. The ideal candidate should be an avid reader of scientific literature, have expert-level hands-on coding experience (e.g., Python, Fortran, or C++), and possess deep expertise and skills in methodology development, which may include contributions to open-source atomistic simulation software packages. While prior knowledge of quantum information and fault-tolerant quantum computing is highly preferred, it is not required.

Responsibilities:

• Conduct theoretical and computational research in materials theory and simulations, advancing methodologies for modeling electronic structure, strongly correlated systems, and emergent quantum phenomena.
• Develop computational workflows that integrate established and emerging techniques, leveraging advances in high-performance computing (HPC), machine learning, and quantum computing.
• Collaborate with quantum algorithm developers, computational physicists, and materials scientists to explore new frontiers in quantum materials modeling.
• Contribute expertise in electronic structure theory and many-body physics to research efforts focused on understanding and predicting material properties.
• Stay at the forefront of developments in computational materials science, incorporating state-of-the-art approaches into research projects.
• Serve as a technical leader in interdisciplinary collaborations, working with internal and external teams on innovative solutions in quantum materials research.
• Engage in external partnerships, scientific discussions, and technical communication to support the broader research and application of advanced computational materials methodologies.
• Document research progress effectively and contribute to publications and external-facing materials that highlight advances in the field.

Experience/Qualifications:

Required:

• Ph.D. in theoretical or computational physics or chemistry or a closely related field, with a focus on electronic structure and many-body physics.
• Strong foundation in electronic structure theory, band structure calculations, and computational modeling.
• Expertise in methodology development within density functional theory (DFT).
• Proficiency in scientific programming and algorithm development, with experience in Python, Fortran, or C++.
• Familiarity with high-performance computing (HPC) environments and large-scale simulations.
• Enthusiasm for interdisciplinary collaboration, working across physics, chemistry, materials science, machine learning, and computational research teams.
• Strong peer-reviewed publication record.

Preferred:

• Experience with machine learning and data-driven approaches in computational modeling.
• Experience with quantum algorithms, particularly their application to materials modeling and electronic structure problems.
• Familiarity with wave function based computational chemistry methodologies, including coupled-cluster, configuration interaction (CI), and multi reference methods.
• Expertise in many-body and strongly correlated systems, including Fermi-Hubbard models, tensor networks, and embedding theories.
• Hands-on coding experience with Wannier function calculations.

PsiQuantum provides equal employment opportunity for all applicants and employees. PsiQuantum does not unlawfully discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, or any other basis protected by applicable laws.

Note: PsiQuantum will only reach out to you using an official PsiQuantum email address and will never ask you for bank account information as part of the interview process. Please report any suspicious activity to recruiting@psiquantum.com.

We are not accepting unsolicited resumes from employment agencies.

About this opportunity:

We are seeking a FP&A Manager to help grow the Freenome Finance team. The FP&A Manager will support planning for key business processes and requires strong financial reporting, forecasting, planning and modeling skills and excellent communication and collaboration skills and business judgment. The ideal candidate is both technically sound and can be a proactive internal consultant, beyond their analytical prowess through their understanding of secondary data, industry knowledge, and track record of innovative and impactful decision support. You will be a strategic architect of our financial future, moving beyond static reporting to provide the actionable insights that drive our commercial scale.

The role reports to the Chief Financial Officer (CFO) and is a critical and high visibility position interacting heavily with the business.

You are passionate about Finance and desire to have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

What you’ll do:

Strategic Business Partnering:

• Serve as the dedicated financial advisor to department heads (R&D, Commercial, Operations), translating complex financial data into a narrative that drives decision-making.
• Identify financial opportunities by deeply understanding the drivers of our diagnostic platform and product offerings.

Proactive Budget Management:

• Drive corporate planning processes through rigorous oversight of departmental budgets and forecasts, ensuring alignment with Freenome’s strategic priorities.
• Empower budget owners with self-service tools while providing the “guardrails” necessary for a public company environment.

Actionable Analysis and Reporting:

• Deliver effective monthly and quarterly reporting that drives accountability, scaled by leveraging technology.
• Establish, track, and report Key Performance Indicators (KPIs) specific to a commercial-stage diagnostic company, such as test volume, ASP, and COGS per test.
• Ensure resources are aligned with strategic and operating priorities and clear financial controls are maintained.
• Identify key business issues that impact short-term and long-range market forecasts; clearly and proactively surface these issues.
• Influence key decisions by delivering high value financial analysis that highlight root causes of variance, trends, and identify actionable opportunities to invest, reduce costs, and mitigate risks.

Systems Innovation and AI Integration:

• Build and refine the forecasting tools, short-term and long-term forecasts models.
• Support the implementation, buildout and continuous improvement of key financial systems, such as ERP, planning and budgeting systems and business Intelligence tools.
• Apply AI and machine learning tools to automate routine reporting and enhance predictive accuracy in our forecasting models.
• Collaborate with the broader organization to drive process and systematic improvements across the Company.

Must haves:

• Bachelor’s degree in Accounting/Finance/Business.
• Minimum of 8 years of progressive Accounting and Finance experience with at least 6 in FP&A and/or business partnering in a fast-paced, high-growth biotech, diagnostic, medical device environment.
• Willingness to roll up your sleeves, handle large amounts of data and build complex financial models.
• Excellent organizational and analytical skills with the ability to creatively solve problems with a data-driven approach.
• Ability to articulate complex financial concepts in understandable terms to non-finance professionals.
• Demonstrated ability to think strategically while maintaining a command of the details.
• Demonstrated ability to develop client group business acumen and provide actionable insights and recommendations to improve KPIs.
• Mastery of Excel and ERP systems (e.g. Netsuite) and proven experience implementing or optimizing FP&A software and a demonstrated interest in AI-driven analytics.
• Passion for automation and continuous improvement to reduce human error and dependency on spreadsheets.
• Proven experience building financial management processes, management reporting, and establishing the financial discipline required in a scaling organization.
• Well-versed in the requirements of a public company and adherence to all applicable laws, rules, and regulations.

Nice to haves:

• MBA/CPA or CFA a plus.
• Experience as a FP&A professional for single-site labs (FDA/CLIA diagnostics business) and/or reagent manufacturing environments.
• Knowledge of clinical diagnostics development, operations, portfolio management and commercial GTM planning.

Benefits and additional information:

The US target range of our base salary for new hires is $146,775 - $183,750. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

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

Applicants have rights under Federal Employment Laws.  

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

#LI-HYBRID

Timing is everything!  If you are passionate about Freenome's mission and want to contribute in a meaningful way, we encourage you to submit your CV or resume.  

About Freenome

Freenome is on a mission to empower everyone with the tools they need to detect, treat, and ultimately prevent diseases. 

By applying advanced machine learning techniques to recent breakthroughs in genomic science, Freenome is developing simple blood tests to detect early-stage cancer and make treatments more effective. The company has raised $238 million from investors such as RA Capital, Polaris Partners, Perceptive Advisors, Andreessen Horowitz, funds and accounts advised by T. Rowe Price Associates, Inc., GV (formerly Google Ventures), Roche Venture Fund, Kaiser Permanente Ventures, American Cancer Society’s BrightEdge Ventures, Data Collective Venture Capital, Novartis and Verily Life Sciences (formerly Google Life Sciences).

Our Science

Freenome is building technology to gain an understanding of the body through several analytes derived from blood. These signals include cell-free DNA, methylation of cell-free DNA, cell-free RNA, circulating proteins, and immune profiling derived from thousands of prospective samples. By developing novel statistical learning methods and applying them to integrate various -omics datasets, Freenome is a leader in modeling specific biological mechanisms to capture disease dependent signatures such as gene expression, immune response, tumor burden, the tissue of origin, and 3D chromatin structure. 

By building comprehensive discovery datasets and modeling critical biological systems, Freenome is learning what biological changes are present within the blood between a variety of different disease states including cancer, autoimmune disorders, infections, drug response, and aging. With the combination of Freenome’s datasets, cross-functional technical expertise, and mission to uncover the biological truth, we seek to positively change the lives of millions through the early detection and early treatment of disease. 

Our Culture

Freenomers are technical and creative, visionary and grounded, empathetic and passionate. We build teams around divergent expertise, which allows us to solve problems and uncover opportunities in unique ways. Freenomers are some of the most talented experts in their fields, coming together to advance healthcare one breakthrough at a time. 

We value empathy, integrity, and trust in one another. That means embracing other’s perspectives, those of our coworkers and those of the patients and communities we serve. It means knowing when to push, and when to listen. At Freenome, we give each other the benefit of the doubt in the belief that we’re all working as a team toward the same goals, and empower others to grow in a collaborative environment. 

What does a successful person look like at Freenome?

Those who thrive at Freenome prioritize, manage, and execute their own goals in alignment with those of the company. They embrace our values of empathy, integrity, and trust, and hold themselves and their team accountable. They crave collaboration with brilliant minds from unfamiliar fields of study and believe that hiring and mentorship are fundamental to our success. Above all, they welcome and provide constructive feedback and criticism, trusting in the good intentions of others, and secure in the knowledge that embracing mistakes is the best way to learn and move on. For those who crave challenges, understudied problems, and the chance to see their work impact the lives of millions of people affected by cancer every year, there’s no better place to be. 

Freenome is proud to be an equal opportunity employer, we value diversity in every way.  Freenome does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law.

About this opportunity:

At Freenome, we are seeking a Sr. Director, Finance to build and shape our Finance team. The ideal candidate will be a strategic and hands-on leader with experience building scalable public company finance organizations. This is a high-impact leadership role responsible for the Financial Planning and Analysis (FP&A), business partnering, and finance operations functions. This role offers a unique opportunity to architect our financial engine. You won’t just be reporting numbers, you will be building the systems, teams and insights that guide our executive team. You will be instrumental in enabling Freenome to bring our early detection tests to patients - changing the entire landscape of cancer.

The role reports to the Chief Financial Officer (CFO). This role will be a Hybrid role based in our Brisbane, California headquarters. 

What you’ll do:

• Accountable for Financial Planning and Analysis, business partnering, and finance operations maintaining clear financial controls and compliance.
• Develop the financial frameworks for our commercial launches, including revenue forecasting, COGS analysis, and go-to-market spend optimization.
• Lead the (AOP) annual operating plan process, rolling quarterly forecasts, and long-range strategic planning models, scaled by technology.
• Build and maintain a detailed financial model to forecast future performance, report budget to actuals.
• Influence key decisions by delivering high value financial analysis that highlight root causes of variance, trends, and identify actionable opportunities to invest, reduce costs, and mitigate risks.
• Create actionable KPI dashboards specific to a commercial-stage diagnostic company, such as test volume, ASP, and COGS per test.
• Increase the speed and efficiency of our FP&A efforts driving the timely delivery, quality, and transparency of information to support business decisions.
• Proactively partner with the senior leadership team and cross-functional stakeholders to align financial objectives with our business strategy and drive key decision-making.
• Identify and manage financial risks monitoring market conditions, developing risk mitigation strategies, and implementing relevant programs.
• Proactive collaboration with leaders within the finance organization to align systems, processes, and initiatives to enable seamless support.
• Drive the implementation, buildout, and continuous improvement of key financial systems, such as ERP, planning and budgeting systems and business intelligence tools.
• Champion the application of AI, machine learning, and automation to increase efficiency and enhance predictive accuracy in our models.
• Lead financial diligence for potential partnerships, acquisitions, or strategic initiatives.
• Participate in audit committee activities as needed.
  

Must haves:

• Bachelor’s degree in finance, accounting, or a related field.
• 12+ years of progressive finance experience in corporate finance, financial modeling, analysis, forecasting, and business partnering.
• 6+ years of experience building, leading, and developing high-performing finance teams.
• Prior leadership as head of the FP&A function at a publicly traded company.
• Strategic mindset with proven ability to align financial strategies with business goals.
• Results-driven and metrics-oriented approach, with a focus on driving growth and proactively mitigating financial risks.
• Sought as a trusted advisor to the business leveraging superior business partnering skills and business acumen.
• Proven ability to effectively manage and deliver multiple, large-scale projects while maintaining business and financial service excellence.
• Consistently monitors the business and markets, adapting where needed to ensure business success.
• Passion for getting in the trenches, leading by example, and influencing process excellence across the organization.
• Exceptional executive communication skills, with a proven ability to distill complex data into clear, concise, and impactful insights to facilitate high-velocity, informed decision making.
  

Nice to haves:

• MBA or CFA preferred.
• Biotech experience preferred.
  

Benefits and additional information:

The US target range of our base salary for new hires is $229,900 - $294,788. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

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

Applicants have rights under Federal Employment Laws.  

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

#LI-HYBRID

About this opportunity:

At Freenome, we are seeking a Senior Machine Learning Research Engineer to join the Machine Learning Science (MLS) team, within the Computational Science department. The ideal candidate has a strong knowledge in designing and building deep learning (DL) pipelines, and expertise in creating reliable, scalable artificial intelligence/machine learning (AI/ML) systems in a cloud environment. 

The MLS team at Freenome develops DL models using massive-scale genomic data that presents significant challenges for current training paradigms. The Senior Machine Learning Research Engineer will primarily be responsible for developing and deploying the infrastructure needed to support development of such DL models: enabling distributed DL pipelines, optimizing hardware utilization for efficient training, and performing model optimizations. As part of an interdisciplinary R&D team, they will work in close collaboration with machine learning scientists, computational biologists and software engineers to accelerate the development of state-of-the-art ML/AI models and help Freenome achieve its mission of reducing cancer mortality via accessible early detection.

The role reports to the Director of Machine Learning Science. This can be a hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you’ll do:

• Implement and refine DL pipelines on distributed computing platforms enhancing the speed and efficiency of DL operations including model training, data handling, model management, and inference.
• Collaborate closely with ML scientists and software engineers to understand current challenges and requirements and ensure that the DL model development pipelines you create are perfectly aligned with scientific goals and operational needs.
• Continuously monitor, evaluate, and optimize DL model training pipelines for performance and scalability.
• Stay up to date with the latest advancements in AI, ML, and related technologies, and quickly learn and adapt new tools and frameworks, if necessary.
• Develop and maintain robust and reproducible DL pipelines that guarantee that DL pipelines can be reliably executed, maintaining consistency and accuracy of results.
• Drive performance improvements across our stack through profiling, optimization, and benchmarking. Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation pipelines.
• Act as a bridge facilitating communication between the engineering and scientific teams, documenting and sharing best practices to foster a culture of learning and continuous improvement.

Must haves:

• MS or equivalent experience in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Software Engineering, with an emphasis on AI/ML theory and/or practical development.
• 5+ years of post-MS industry experience working on developing AI/ML software engineering pipelines.
• Proficiency in a general-purpose programming language: Python (preferred), Java, Julia, C, C++, etc.
• Strong knowledge of ML and DL fundamentals and hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, Jax or Scikit-learn.
• In-depth knowledge of scalable and distributed computing platforms that support complex model training (such as Ray or DeepSpeed) and their integration with ML developer tools like TensorBoard, Wandb, or MLflow.
• Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and how to deploy and manage AI/ML models and pipelines in a cloud environment.
• Understanding of containerization technologies (e.g., Docker) and computing resource orchestration tools (e.g., Kubernetes) for deploying scalable ML/AI solutions.
• Proven track record of developing and optimizing workflows for training DL models, large language models (LLMs), or similar for problems with high data complexity and volume.
• Experience managing large datasets, including data storage (such as HDFS or Parquet on S3), retrieval, and efficient data processing techniques (via libraries and executors such as PyArrow and Spark).
• Proficiency in version control systems (e.g., Git) and continuous integration/continuous deployment (CI/CD) practices to maintain code quality and automate development workflows.
• Expertise in building and launching large-scale ML frameworks in a scientific environment that supports the needs of a research team.
• Excellent ability to work effectively with cross-functional teams and communicate across disciplines. 
  

Nice to haves:

• Experience working with large-scale genomics or biological datasets.
• Experience managing multimodal datasets, such as combinations of sequence, text, image, and other data.
• Experience GPU/Accelerator programming and kernel development (such as CUDA, Triton or XLA).
• Experience with infrastructure-as-code and configuration management.
• Experience cultivating MLOps and ML infrastructure best practices, especially around reliability, provisioning and monitoring.
• Strong track record of contributions to relevant DL projects, e.g. on github.
  

Benefits and additional information:

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

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

Applicants have rights under Federal Employment Laws.  

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

#LI-REMOTE

About this opportunity:

At Freenome, we are seeking a Senior Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) methods, a track record of successfully using these methods to answer complex research questions, and the ability to thrive in a highly cross-functional environment.

They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you’ll do:

• Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.).
• Build new models or fine-tune existing models to identify biological changes resulting from disease.
• Build models that achieve high accuracy and that generalize robustly to new data.
• Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms.
• Work closely with ML Engineering partners to ensure that Freenome’s computational infrastructure supports optimal model training and iteration.
• Take a mindful, transparent, and humane approach to your work.

Must haves:

• PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics.
• 3+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.
• Expertise, demonstrated by research publications or industry achievements, in applied machine learning, deep learning and complex data modeling.
• Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks.
• Practical and theoretical understanding of DL models like large language models or other foundation models.
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data.
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
• Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face.
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases.
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations.
• A passion for innovation and demonstrated initiative in tackling new areas of research.

Nice to haves:

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field.
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models.
• Experience in NGS data analysis and bioinformatic pipelines.
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS.
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems.

Benefits and additional information:

The US target range of our base salary/hourly rate for new hires is $173,775 - $246,750. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

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

Applicants have rights under Federal Employment Laws.  

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

#LI-HYBRID

About this opportunity:

Freenome is seeking a highly analytical and systems-savvy Senior People Systems and Data Analyst to elevate our People data capabilities and drive insight-led decision-making. This role will own the development of dashboards, analytics, and reporting that provide visibility into workforce trends and inform hiring, retention, engagement, and organizational planning strategies. This individual will transform People data into actionable insights through advanced analytics, scalable dashboards, and strong data storytelling. While the role maintains ownership of People systems and data integrity, its primary focus is generating insights that enable better business decisions.

The role reports to the Director, People Operations. This role will be a Hybrid role.  

What you’ll do:

• Develop, analyze, and interpret workforce data to identify trends, risks, and opportunities across recruiting, retention, performance, and engagement.
• Conduct deep-dive analyses (attrition trends, hiring funnel performance, compensation insights, engagement drivers).
• Build statistical and trend analyses across the employee lifecycle to proactively surface insights that influence People and business decisions.
• Deliver actionable quarterly reporting that translates complex datasets into clear, executive-ready insights and recommendations.
• Design, build, and maintain scalable and automated dashboards.
• Establish consistent KPI definitions and reporting standards.
• Improve data visualization practices to ensure clarity, usability, and impact.
• Replace manual reporting processes with automated, real-time reporting solutions.
• Ensure high levels of data accuracy, integrity, and trust.
• Serve as primary People data and HRIS reporting expert.
• Partner with IT and vendors to implement and manage integrations, evaluate new features, and identify opportunities to automate data workflows.
• Manage data governance standards to ensure compliance and data privacy best practices.
• Identify process improvements that enhance efficiency, data structure and accessibility.
• Enable tier-zero employee and manager self-service for policies, processes, and data through systems and chatbots, reducing reliance on People team members and ticket systems.
• Champion system education to drive employee and manager self-service adoption and data and systems utilization.
• Drive AI initiatives such as deploying LLMs for job descriptions and ML to forecast attrition, ensuring tools are trained and continuously refined to be fit-for-purpose and remain within ethical and legal guardrails.
  

Must haves:

• Bachelor’s degree in Statistics, Data Science, Business Analytics, HR, Economics, or related field.
• 5–7 years of experience in People Analytics, Workforce Analytics, HRIS Analytics, or related analytical roles.
• Prior experience modifying, improving and/or implementing People systems (Greenhouse, Paylocity a bonus).
• Advanced proficiency in data visualization tools (Tableau, Power BI, Looker, or similar).
• Strong experience building executive dashboards from the ground up.
• Knowledge of data, statistical, and predictive analysis.
• Advanced Excel/Google Sheets skills.
• Experience working with large, complex datasets.
• Demonstrated ability to translate data into clear business insights and recommendations.
• Strong understanding of core People processes (recruiting, compensation, performance, engagement, workforce planning).
• Excellent verbal and written communication skills.
• Strong analytical and problem-solving skills.
• Passion for driving continuous improvement simplifying workflows, implementing automation, and driving self-service.
• Demonstrated interest in leveraging AI to enhance systems and analytics.
  

Nice to haves:

• Experience in a high-growth biotech or startup environment, with exposure to IPO preparation, public company reporting requirements, or SOX-compliant processes.
• Familiarity with Greenhouse, Paylocity, or other HRIS/ATS platforms.
• Exposure to predictive analytics or basic modeling techniques.
• SHRM-CP or SHRM-SCP certification.
  

Benefits and additional information:

The US target range of our base salary for new hires is $120,275 - $170,100. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

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

Applicants have rights under Federal Employment Laws.  

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

#LI-HYBRID

About this opportunity:

At Freenome, we are seeking a Staff Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) methods, a track record of successfully using these methods to answer complex research questions, the ability to drive independent research and thrive in a highly cross-functional environment.

They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you’ll do:

• Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.).
  
• Build new models or fine-tune existing models to identify biological changes resulting from disease.
  
• Build models that achieve high accuracy and that generalize robustly to new data.
  
• Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms.
  
• Work closely with ML Engineering partners to ensure that Freenome’s computational infrastructure supports optimal model training and iteration.
  
• Take a mindful, transparent, and humane approach to your work.
  

Must haves:

• PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics.
• 6+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.
• Expertise demonstrated by research publications or industry achievements, in driving independent research in applied machine learning, deep learning and complex data modeling.
• Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks, boosting and model aggregation.
• Practical and theoretical understanding of DL models like large language models or other foundation models.
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data.
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
• Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face.
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases.
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations.
• Proficient at productive cross-functional scientific communication and collaboration with software engineers and computational biologists.
• A passion for innovation and demonstrated initiative in tackling new areas of research.

Nice to haves:

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field.
  
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models.
  
• Experience in NGS data analysis and bioinformatic pipelines.
  
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS.
  
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems.
  

Benefits and additional information:

The US target range of our base salary for new hires is $199,675.00 - $283,500.00. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

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

Applicants have rights under Federal Employment Laws.  

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

#LI-HYBRID

Role

The Director, Business Development is a senior individual contributor responsible for sourcing, advancing, and closing strategic partnerships pharmaceutical companies. This role carries a significant individual bookings target and is accountable for building and converting a high-quality pipeline aligned with Vivodyne’s commercial priorities.

The Director, BD  will operate with a high degree of autonomy and strategic judgment; owning account strategy, shaping deal structures, and leading cross-functional execution across Science, Bio, Legal, and Finance. Success in this role requires balancing hands-on deal execution with thoughtful account planning and market insight.

Responsibilities

Ownership & Deal Execution

• Carry and deliver against an individual quarterly and annual bookings target.

• Source, qualify, and advance new partnership opportunities with mid-sized and large pharma companies and AI/data-centric partners.

• Lead opportunities through the full deal lifecycle: discovery → scoping → proposal → negotiation → close.

• Shape opportunity-specific deal structures including pilot studies, discovery programs, efficacy/tox engagements, and data-enabled collaborations.

• Own follow-through and momentum on active deals to ensure timely progression and closure.

• Run weekly pipeline reviews to reduce slippage, re-qualify deals, and improve forecast accuracy.
  
  

Account Strategy & Pipeline Management

• Develop and execute account-level strategies for a defined set of target and active accounts.

• Build and maintain a robust personal pipeline aligned with revenue goals and priority therapeutic areas.

• Conduct stakeholder mapping to identify scientific, operational, and commercial decision-makers and influencers.

• Expand existing accounts by identifying adjacent research groups, new use cases, or follow-on program opportunities.

• Maintain accurate CRM hygiene, deal staging, and pipeline updates.
  
  

Strategic Contribution 

• Translate Vivodyne’s platform capabilities into tailored value propositions aligned to customer discovery-stage needs.

• Provide structured market and customer feedback to inform leadership, product positioning, and messaging.

• Contribute to the evolution of deal archetypes, pricing approaches, and engagement models based on learnings.

• Collaborate with Marketing and Bio teams to refine scientific narratives and customer-facing materials.

• Deliver structured market and customer intelligence to leadership to refine positioning, pricing/deal archetypes, and therapeutic-area prioritization.

Cross-Functional Deal Leadership

• Quarterback cross-functional deal teams, coordinating inputs from Science, Bio, Legal, and Finance.

• Ensure technical feasibility and resourcing alignment before advancing proposals.

• Partner with Legal and Finance during contracting and commercial negotiations.

• Communicate deal status, risks, and forecast updates clearly to BD and company leadership.

• Lead contracting and commercial negotiations to close efficiently (anticipate pharma procurement/legal patterns, manage redlines/risks, drive velocity through clear negotiation strategy).
  
  

Event  Engagement

• Represent Vivodyne at key industry conferences and scientific meetings.

• Execute targeted meeting strategies and follow-up plans to support personal pipeline goals.

• Participate in seminars, site visits, and customer-facing scientific discussions as needed.

• Capture and operationalize field intel from conferences (themes, objections, competitor claims) into messaging updates and enablement for the broader BD/GTM team.

• Execute rigorous post-event follow-up with clear conversion targets to advance opportunities toward close.

Requirements

Required

• 7–10+ years of business development or alliance experience in biotech or pharma.

• Proven success carrying an individual quota and closing complex, multi-stakeholder deals.

• Experience supporting or working within discovery platforms, preclinical services, or advanced research.

• Strong understanding of drug discovery workflows and customer decision dynamics.

• Ability to translate complex science into clear, customer-aligned value propositions.

• Highly organized, with experience managing end to end sales cycles and a sizable personal pipeline.
  
  

Preferred

• Familiarity with oncology discovery, RNA modalities, and/or preclinical toxicology.

• Exposure to AI/ML-enabled discovery or data-driven collaboration models.

• Experience working with novel or emerging platform technologies.
  

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.

Role

As a Principal Mechanical Engineer at Vivodyne, you will be part of a multi-disciplinary team pushing the boundaries of automated, large-scale "organ-on-a-chip" robotics and related manufacturing systems. Your focus will be on developing and optimizing hardware and software that orchestrates robotic arms, embedded controllers, and microfluidic systems to enable high-throughput, high-precision biological workflows.

This role requires expertise across hardware and software, but primarily hardware.  From high-level motion control and machine vision to robotics programming and embedded firmware. You’ll work extensively with existing Python (less so with, C#, and C++) codebases, ensuring seamless system integration and performance.

You are a mechanical design expert.  Things like kinematic docking, 440 vs 316, FEA, and error budgets are very familiar to you.  Your friends include McMaster-Carr, Misumi, and Grainger. 

Collaboration is key—you’ll engage with mechanical engineers, biologists, immunologists, AI scientists, and process engineers to design and refine automation workflows that drive breakthroughs. We’re looking for a problem solver comfortable working across multiple domains, thriving in a fast-paced, high-innovation environment that values continuous learning and technical excellence.

This is a full-time, onsite role in San Francisco, where you’ll be designing, building, and testing some of the most advanced automation and high-throughput biology systems in the world.

Responsibilities

• Architect, design, and implement advanced automation systems, ranging from automated microfluidic manufacturing to high-precision mammalian cell culture platforms—all of which are mission-critical and highly visible both internally and externally.
• Develop hardware and software systems that acquire and process data reliably, ensuring smooth handoffs to production through rigorous documentation, data acquisition, and analysis.
• Embrace the dynamic nature of a rapidly growing startup, working across multiple projects and disciplines.
• Collaborate cross-functionally with Product leads, tissue engineers, microfluidics specialists, and AI researchers etc. to gather requirements, set technical objectives, and integrate new features into our robotics platforms.
• Design and implement resilience mechanisms to ensure system robustness, enabling fault detection, fault recovery, and minimal downtime, while maintaining data integrity.
• Proactively identify optimization opportunities, selecting priorities through engineering analysis and data-driven decision-making.
• Communicate progress and findings to internal stakeholders—including mechanical engineers, data scientists, and senior leadership—through data-laden presentations and technical reports.

Requirements and Expectations

Technical Expertise & Knowledge

• Bachelor’s degree (M.S. or Ph.D. preferred) in Mechanical Engineering, Chemical Engineering, or a related field with a focus on microfluidics, tissue engineering, or lab automation at least six years of directly relevant industry experience.
• Broad experience in hardware and, preferable, software design for automation, spanning off-the-shelf solutions and custom-built systems—you have developed complex automation workflows for production-level environments.
• Proficiency in key hardware and software tools, including SolidWorks (expert-level, CAM experience is a plus), and at some exposure to Python/Matlab/C++/C#/Javascript/etc.
• Hands-on experience with commonly used automation hardware, such as vision/camera systems (optics and/or optomechanical expertise is a plus), motion control, liquid handling, and pick-and-place robotics.
• Highly knowledgeable in various Manufacturing Technologies, you know how things are made and which approaches fit a particular application
• Industry-specific expertise is highly valued:
• Biotech/lab automation or semiconductor robotics experience is a strong advantage.
• Knowledge of microfluidics and fluid handling systems.
• Experience integrating robotics with high-content imaging and confocal microscopy systems, optimizing workflows for advanced imaging pipelines.
• Biology background or familiarity with cell and tissue engineering concepts is a significant plus, especially in handling biological samples.
• Bonus points for experience with:
• Electronics/PCBA design or basic knowledge (reading schematic, troubleshooting interconnects), statistical analysis/data collection to inform design performance rigorously

Problem Solving & Ownership

• You take an outcome-driven approach, translating project goals and technical challenges into systematic, resilient robotics solutions.
• Strong ownership mentality, ensuring the timely delivery of high-reliability features and improvements.
• Growth-oriented, continuously seeking ways to enhance automation processes, optimize robotic operations, and drive innovation.

Collaboration & Communication

• A team player, capable of working with engineers, scientists, and external stakeholders to define requirements, refine designs, and communicate project progress effectively.
• Clear communicator, able to explain complex robotics concepts to cross-functional teams, from software engineers to biologists.
• Interdisciplinary mindset, integrating feedback from various fields to develop thoughtful, iterative design improvements.

Innovation & Leadership Mindset

• Passionate about staying at the cutting edge of robotics, bringing fresh ideas from emerging technologies, best practices, and research to the team.
• Comfortable taking initiative in uncharted territories, whether it’s developing new motion-planning algorithms or integrating novel sensors and hardware.

Why Vivodyne?

• High-Impact Mission – Play a pivotal role in transforming drug discovery and human therapeutics through advanced robotics and automation.
• Multi-Disciplinary Exposure – Work alongside leading experts in robotics, AI, biology, and microfluidics, expanding your expertise in a truly collaborative setting.
• Growth Opportunities – A fast-growing startup environment with significant autonomy, ownership, and influence over best practices in the intersection of biotech and robotics.
• Innovative Culture – Join a team that prioritizes continuous learning, rigorous engineering and scientific standards, and bold problem-solving.

If you're excited about revolutionizing automation in organoid engineering and biotech—while pushing the boundaries of robotics, AI, and advanced systems—let’s connect! Please submit your resume and a brief statement of interest. We look forward to exploring the opportunity together.

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.

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.