Role

We’re looking for an exceptional Senior Full-Stack Software Engineer to work hand in hand with our Product team to build polished, high-performance web applications using React with FastAPI on the backend and Postgres as a database.

The ideal candidate leads with deep frontend expertise in building sophisticated, stateful UIs in React/TypeScript, while bringing enough backend fluency to own features end-to-end. You'll build rich, data-dense interfaces for scientific workflows where getting the interaction design and state management right is the hard part. Additionally, the ideal candidate is an 'AI native' and uses their strong technical expertise to augment the prototyping speed provided by LLMs. You'll ship deliverables in days, not months, and have a sharp instinct for system architectures that achieve rapid delivery and robust performance.

You will be a core contributor to shaping our next-generation biotech platform that discovers and tests new drugs on lab-grown human tissues.

Own the building of scientific experiment design and results-monitoring tools that, together with our platform, have enabled Vivodyne to partner with a majority of the top-10 pharmaceutical companies in making better, safer cures to complex human diseases. You will be expected to deliver web applications that align with well-designed frames/user flows and product requirements that help scientists interact seamlessly with our unique datasets, robotic systems, and lab-grown tissues.

You’ll have the opportunity to work at the cutting edge of biotech and software engineering, collaborating with teams spanning tissue engineering, robotics, and AI. You'll be working a few feet away from large precision robots, laser microscopes, and robot arms, surrounded by an exceptionally talent-dense team of experts from multiple scientific disciplines.

You will be able to focus on building internal products and tools with incredible functionality, surrounded by sophisticated end users directly appreciative of the products you build---without needing to do integration testing for first-gen Chromebooks or handle bug reports from Fire tablets.

While bringing a passion and exquisite skill for building and shipping high-quality applications that drive scientific discovery, you'll be involved firsthand in the advancement of human health, you'll watch thousands of human organ tissues grow before your eyes, and join an intense, fun, fast-moving team in shaping the future of human health.

Responsibilities

Frontend-Led Full-Stack Development — Architect and build complex React/TypeScript interfaces for scientific workflow applications; own backend integration points via API design and data layer work in Postgres.

User Experience — Create clean, responsive, and user-focused interfaces that translate complex requirements into intuitive designs, establishing best practices for component architecture and state management patterns.

Code Quality & Best Practices — Write well-tested, maintainable code with a focus on scalability, performance, and cost-efficiency.

Collaboration & Communication — Work closely with scientists, engineers, and AI researchers to gather requirements, provide updates, and deliver impactful solutions.

High Velocity / AI Accelerated Development — Leverage leading language models and agentic tools like Claude Code and Codex, or similar to ship reliable code quickly; maximize prototyping and component design velocity while balancing robustness of implementations

Requirements and Expectations

Technical Excellence

• Deep expertise in React, TypeScript, and modern frontend architecture (component composition, state management, performance profiling). 
• Proficient in building visually appealing, high-performance React applications.
• Strong CSS/styling architectural skills (CSS modules, Tailwind etc.)
• Strong data modeling skills for biotech applications, translating scientific needs into structured schemas.
• Comfortable in API design, schema definition, and query optimization with Postgres.
• Solid foundation in data structures, algorithms, and software architecture (CS degree preferred).

Accountability & Problem-Solving

• Own full-stack development, ensuring high-quality, tested, and timely feature delivery.
• Balance speed and rigor to solve complex engineering challenges, from large-scale data ingestion to optimizing imagery metadata.

Collaboration & Communication

• Work cross-functionally with scientists, engineers, and AI researchers, aligning technical solutions with user needs.
• Keep end-users in mind, delivering intuitive, efficient workflows.

Delivering Results

• Manage time effectively, handling multiple priorities while shipping production-ready features.
• Champion best practices, maintain clear documentation, and uphold high coding standards.

Architecture & Design

• Design scalable, reliable systems while anticipating and addressing bottlenecks.
• Leverage open-source and existing frameworks to optimize development.

Leadership & Influence

• Mentor junior engineers through code reviews and knowledge sharing.
• Advocate for full-stack best practices to drive scientific and business impact.

Qualifications

• Bachelor’s or Master’s in Computer Science (or related field), or equivalent experience.
• 5+ years building complex React applications with sophisticated state management, not just simple CRUD interfaces.
• Fluency in TypeScript. Knowledge of TanStack ecosystem is a bonus.
• Experience Developing Applications that Render and Annotate Imagery is highly valued.
• Comfortable working with APIs and understanding the data layer.
• Working knowledge of Python (e.g. Pydantic, FastAPI).
• Working knowledge of Postgres in production environments.
• Experience in High-throughput Laboratory Automation or Robotics is highly valued.
• Excellent Communication Skills for conveying technical concepts and aligning stakeholder expectations.
• Project Delivery Experience in fast-paced environments; comfortable balancing shifting priorities and multiple projects.
• Proven Ability to collaborate across disciplines, from biology to automation to AI, delivering high-impact results.
• Track Record of shipping secure, maintainable, and well-tested code.

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 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.

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.