Vivodyne creates human data before clinical trials.
We accelerate the successful discovery, design, and development of human therapeutics by testing on large, lab-grown human organ tissues at massive scale, driving technological advancement at the convergence of novel biology, robotics, and AI. We identify and validate new therapeutic targets and de-risk new therapeutic assets by producing clinically translatable multi-omic data from our proprietary, physiologically-realistic human organ tissues at unprecedented scale, speed, and quality. This enables us to produce more human data than all clinical trials in the U.S. combined. We’re financially backed by some of the most selective and successful venture funds, and we have already partnered with a majority of the top 10 multinational pharmaceutical companies to discover and develop better, safer drugs and dramatically reduce the burden of animal testing.
www.vivodyne.com
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 platform
- s. 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 analys
- is. 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 soluti
- ons. 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 methodolo
- gies. Scalability & Efficiency{{:}} Emphasize modularity, composability, and performance efficiency in designing and implementing high-throughput compute and analytics pipe
- lines. 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 exp
ertise. Requirements and Expe
- ctationsScientific 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 i
- nnovation.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 consen
- sus-building.Delivering Results{{:}} Prioritize impactful research, using project management best practices to track progress, mitigate risks, and m
- eet deadlines.Architecture & Coding{{:}} Design scalable, cost-effective systems and produce clean, well-documented code with continuous testing and governa
- nce 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 indu
stry discussio
- ns.QualificationsEducation
- & Experience PhD in Computer Science, Applied Mathematics, or a related field, or equivalent prac
- tical experience.Proven expertise developing and deploying advanced ML architectures (Transformers, Diffusion, multi-modal models) in Genera
- tive AI settings.Demonstrated history of success with image processing and large-scal
- e model training.
- Technical Skills Strong knowledge of AWS or another major cloud provider for MLOps, big data processing, and sc
- alable computing.Experience building models for petabyte-scale datasets and understanding the associated architectural and operatio
- nal complexities.Domain Exper
- tise (Preferred) Familiarity with biological or biomedical imaging; advanced knowledge in multi-modal Phenomaps, especially integrating imagery with multi-omics data,
- is a major plus.Additiona
- l Desired Skills Prior experience with HPC, GPU clusters, or distributed comp
- uting frameworks.Comfortable with container orchestration and open-source data engineeri
- ng/ML frameworks.Soft Skills
- & Leadership Strong written and oral communication skills, with a proven ability to present complex technical topic
- s to non-experts.Demonstrated ability to thrive in ambiguous environments, driving clarity and direction with min
imal supervision.San Francisco pay range{{:}} $220,000 USD - $270,000 USD
