The Team

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

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

The Opportunity

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

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

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

What You'll Do

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

What You'll Bring

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

Compensation

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

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

Better Together

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

Benefits for the Whole You 

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

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

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

#LI-Hybrid 

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join our Team!

As an ML Engineer, you'll join some of the strongest infrastructure engineers in AI, building the systems that connect everything together. The infrastructure problems you solve directly determine what science becomes possible. 

What You'll Do

• Work with high-dimensional scientific data formats and contribute to backend compatibility, format evaluation, and I/O performance benchmarking at petabyte scale.
• Define and shape the engineering patterns your team and collaborating researchers will build on for years; the abstractions you write today become the foundation others depend on at scale.
• Work at the intersection of AI systems and biological discovery, where the infrastructure problems you solve directly determine what science becomes possible.
• Deploy models to production and manage artifact tracking across models and datasets.
• Design and optimize GPU-native data loading pipelines for large-scale multi-dimensional tensor workloads, including profiling and resolving hardware utilization bottlenecks across multi-backend systems.
• Work on simplification and improvement of codebase abstractions to accelerate research momentum.
• Build and maintain primitives for pre-training infrastructure that ensure the reliability and continuity of large-scale training runs.
• Help cultivate best practices in MLOps, and think about the full ML lifecycle, including data, fine-tuning, deployment, reliability and monitoring.
• Possesses the ability to execute complex modifications to the research pipeline, such as fast data loading and distributed training.
• Handle DevOps responsibilities, focused on making all engineers and researchers more productive. This includes tasks like cluster monitoring, unit testing and integration testing of research codebase, and continuous integration.
• Collaborate with partner researchers and engineers to deploy our technology within external infrastructure.

What You'll Bring

• Hands-on experience with PyTorch, including custom training loops, distributed training, or low-level performance work.
• Familiarity with GPU-native data I/O tools and large-scale tensor formats (e.g. Zarr, HDF5, TensorStore, or similar).
• Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Experience building or working with AI agent frameworks is a plus.
• A track record of building systems that other engineers and researchers depend on. Not just running experiments, but shipping infrastructure that scales.

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $150,000 to $350,000+ annually. Compensation ranges will vary based on job-related skills, level of experience, and knowledge. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.

Benefits for the Whole You 

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

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

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join our Team!

As an ML Engineer, you'll join some of the strongest infrastructure engineers in AI, building the systems that connect everything together. The infrastructure problems you solve directly determine what science becomes possible. 

What You'll Do

• Work with high-dimensional scientific data formats and contribute to backend compatibility, format evaluation, and I/O performance benchmarking at petabyte scale.
• Define and shape the engineering patterns your team and collaborating researchers will build on for years; the abstractions you write today become the foundation others depend on at scale.
• Work at the intersection of AI systems and biological discovery, where the infrastructure problems you solve directly determine what science becomes possible.
• Deploy models to production and manage artifact tracking across models and datasets.
• Design and optimize GPU-native data loading pipelines for large-scale multi-dimensional tensor workloads, including profiling and resolving hardware utilization bottlenecks across multi-backend systems.
• Work on simplification and improvement of codebase abstractions to accelerate research momentum.
• Build and maintain primitives for pre-training infrastructure that ensure the reliability and continuity of large-scale training runs.
• Help cultivate best practices in MLOps, and think about the full ML lifecycle, including data, fine-tuning, deployment, reliability and monitoring.
• Possesses the ability to execute complex modifications to the research pipeline, such as fast data loading and distributed training.
• Handle DevOps responsibilities, focused on making all engineers and researchers more productive. This includes tasks like cluster monitoring, unit testing and integration testing of research codebase, and continuous integration.
• Collaborate with partner researchers and engineers to deploy our technology within external infrastructure.

What You'll Bring

• Hands-on experience with PyTorch, including custom training loops, distributed training, or low-level performance work.
• Familiarity with GPU-native data I/O tools and large-scale tensor formats (e.g. Zarr, HDF5, TensorStore, or similar).
• Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Experience building or working with AI agent frameworks is a plus.
• A track record of building systems that other engineers and researchers depend on. Not just running experiments, but shipping infrastructure that scales.

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $150,000 to $350,000+ annually. Compensation ranges will vary based on job-related skills, level of experience, and knowledge. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.

Benefits for the Whole You 

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

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

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join Our Team!

As a Research Scientist, you'll build the models and systems that define what AI can do in biology: foundation models, reasoning, reinforcement learning, and multi-agent systems at frontier scale.

What You'll Do

• Build on and advance the AI systems at the frontier of biology to accelerate science
• Design novel model architectures and scale pre-training pipelines for our biology foundation models.
• Build post-training systems that drive biological discovery: RL, reward modeling, reasoning, and multi-agent orchestration for long-horizon scientific tasks.
• Design evaluation frameworks and AI systems with scientists across Biohub and beyond, grounded in real biological outcomes and real world impact.
• Engage the wider scientific community through impactful publications, open-source releases, and collaborations worldwide.

What You'll Bring

• PhD in computer science or a related field, or equivalent experience
• Significant experience building and scaling deep learning systems, ideally in research-driven environments
• Strong engineering and scientific fundamentals
• Comfort with ambiguity, rapid iteration, and loosely-defined research problems
• Strong communication skills across technical and scientific audiences

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $214,000 to $375,000 annually. Final compensation is based on the level at which you are hired. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

Benefits for the Whole You 

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

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

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid 

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join Our Team!

As a Research Engineer, you'll build the models and systems that define what AI can do in biology: foundation models, reasoning, reinforcement learning, and multi-agent systems at frontier scale.

What You'll Do

• Build on and advance the AI systems at the frontier of biology to accelerate science
• Design novel model architectures and scale pre-training pipelines for our biology foundation models.
• Build post-training systems that drive biological discovery: RL, reward modeling, reasoning, and multi-agent orchestration for long-horizon scientific tasks.
• Design evaluation frameworks and AI systems with scientists across Biohub and beyond, grounded in real biological outcomes and real world impact.
• Engage the wider scientific community through impactful publications, open-source releases, and collaborations worldwide.

What You'll Bring

• Significant experience building and scaling deep learning systems, ideally in research-driven environments
• Strong engineering and scientific fundamentals
• Comfort with ambiguity, rapid iteration, and loosely-defined research problems
• Strong communication skills across technical and scientific audiences

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $214,000 to $375,000 annually. Final compensation is based on the level at which you are hired. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

Benefits for the Whole You 

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

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

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join Our Team!

As a Research Engineer, you'll build the models and systems that define what AI can do in biology: foundation models, reasoning, reinforcement learning, and multi-agent systems at frontier scale.

What You'll Do

• Build on and advance the AI systems at the frontier of biology to accelerate science
• Design novel model architectures and scale pre-training pipelines for our biology foundation models.
• Build post-training systems that drive biological discovery: RL, reward modeling, reasoning, and multi-agent orchestration for long-horizon scientific tasks.
• Design evaluation frameworks and AI systems with scientists across Biohub and beyond, grounded in real biological outcomes and real world impact.
• Engage the wider scientific community through impactful publications, open-source releases, and collaborations worldwide.

What You'll Bring

• Significant experience building and scaling deep learning systems, ideally in research-driven environments
• Strong engineering and scientific fundamentals
• Comfort with ambiguity, rapid iteration, and loosely-defined research problems
• Strong communication skills across technical and scientific audiences

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $214,000 to $375,000 annually. Final compensation is based on the level at which you are hired. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.

Benefits for the Whole You 

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

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

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join Our Team!

As a Research Scientist, you'll build the models and systems that define what AI can do in biology: foundation models, reasoning, reinforcement learning, and multi-agent systems at frontier scale.

What You'll Do

• Build on and advance the AI systems at the frontier of biology to accelerate science
• Design novel model architectures and scale pre-training pipelines for our biology foundation models.
• Build post-training systems that drive biological discovery: RL, reward modeling, reasoning, and multi-agent orchestration for long-horizon scientific tasks.
• Design evaluation frameworks and AI systems with scientists across Biohub and beyond, grounded in real biological outcomes and real world impact.
• Engage the wider scientific community through impactful publications, open-source releases, and collaborations worldwide.

What You'll Bring

• PhD in computer science or a related field, or equivalent experience
• Significant experience building and scaling deep learning systems, ideally in research-driven environments
• Strong engineering and scientific fundamentals
• Comfort with ambiguity, rapid iteration, and loosely-defined research problems
• Strong communication skills across technical and scientific audiences

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $214,000 to $375,000 annually. Final compensation is based on the level at which you are hired. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.

Benefits for the Whole You 

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

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

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid 

The Team

Biohub is leading the new era of AI-powered biology to cure or prevent disease through its 501c3 medical research organization, with the support of the Chan Zuckerberg Initiative.

Within Biohub, Bioengineering is a team of engineers with a diverse set of skills, including electronics, optics, imaging, automation, mechatronics, fluidics, software development, etc. We design and build custom instrumentation and automation systems to support the Biohub’s scientific mission.

The Opportunity

We are seeking an experienced Lab Automation Applications Engineer to design, develop, and maintain automated protocols that support cell biology research programs. This role is ideal for an automation professional who can independently lead protocol development projects, optimize workflows, and serve as a technical resource for researchers. You will work closely with research scientists, hardware and software engineers, data scientists, laboratory staff, and facility managers to develop automation protocols that enhance throughput, reproducibility, and data quality. In this role, you will take ownership of end-to-end automation protocols, from initial method development through validation, production deployment, quality control and performance monitoring. You will also help drive continuous improvement of our automation capabilities.

What You'll Do

• Lead the design, development, testing, and validation of automated protocols for cell biology (including multi-day cell culture and passaging), cell imaging, and molecular biology.
• Independently program and optimize methods on Hamilton STAR/Vantage platforms using VENUS software, and other platforms, such as Opentrons and Agilent Bravos.
• Partner with research scientists and technology teams to scope automation protocols, define requirements, and deliver solutions that meet scientific and throughput goals.
• Develop and maintain robust quality control processes for automated workflows, including run validation, error handling, and performance monitoring.
• Create and maintain comprehensive documentation including method specifications, SOPs, validation reports, and training materials.
• Troubleshoot and resolve, in collaboration with hardware and software engineers and/or scientists, complex hardware, software, and method issues.
• Manage vendor relationships for maintenance and support.
• Mentor junior automation engineers and contribute to the team's technical growth and best practices.
• Identify and implement process improvements that increase throughput, reliability, and data quality across the automation platform.

What You'll Bring

Essential

• Bachelor's degree in Engineering, Biology, Biochemistry, or related field.
• 5+ years of hands-on experience with laboratory automation in a biology research or industrial biotech environment.
• Demonstrated expertise programming and running automated liquid handling systems. Experience with Hamilton STAR and Vantage liquid handlers and the VENUS software are a big plus.
• Experience with robotic arms, robot programming, PLC systems, or motion control
• Experience integrating liquid handlers with peripheral lab instruments and scheduling systems.
• Proficiency in Python or another scripting language for automation support, data analysis, or custom tooling.
• Strong understanding of molecular biology, biochemistry, and cell biology laboratory techniques.
• Demonstrated ability to independently manage projects from concept through deployment.
• Demonstrated experience with proper documentation of protocols and operating procedures, performance/quality control metrics, etc.
• Commitment to reproducible research practices and rigorous documentation
• Demonstrated ability to think creatively and work independently.
• Excellent problem-solving skills and the ability to quickly adapt to new technological challenges and troubleshoot complex technical problems.
• Eager to learn new methods, protocols and technologies.
• Strong communication and interpersonal skills.
• Highly collaborative spirit and strong teamwork skills.

Nice to Have

• Experience with live cell imaging
• Experience with laboratory data management systems (e.g., LIMS, ELN)
• Knowledge of data analysis, statistical methods, and workflow management software

Compensation

The San Francisco, CA base pay range for a new hire in this role is $190,000.00 - $261,800.00. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

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

Better Together

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

Benefits for the Whole You 

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

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

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

#LI-Hybrid

The Team

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

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

The Opportunity

The Data Engineering and Infrastructure team brings AI/ML technology and Data to the table in new ways to help drive AI powered solutions that accelerate Biomedical research. We are uniquely positioned to design, build, and scale software systems to help scientists better address the myriad challenges they face. We are supporting researchers and scientists around the world by developing the capacity to apply state-of-the-art methods in artificial intelligence and machine learning to solve important problems in the biomedical sciences.

This team works on building shared tools and platforms to be used across Biohub, partnering and supporting the work of an extensive group of Research Scientists, Data Scientists, AI Research Scientists, and Computational Biologists. Members of the shared infrastructure engineering team have an impact on all of Biohub’s initiatives by enabling the technology solutions used by other engineering teams to build a frontier model and scale the feedback loop.

What You'll Do

• Develop and maintain the tooling and infrastructure that drives the entire data lifecycle at Biohub, from ingestion and processing to secure storage and access. Your work will directly support cutting-edge research, AI model training, and data analysis across the organization.
• Partner with researchers and engineers across various domains, including genetics, imaging, and scientific literature. You'll work on various use cases, from web analytics to complex model training, ensuring data accessibility and performance for teams across CZI.
• Design and implement flexible, scalable, and performant systems to address our stakeholders’ needs, leveraging technologies like Argo Workflows, Slurm, Ray, AWS Parallel Cluster for mass-scale job processing and orchestration; Vast Data, Delta Lake, Databricks and Apache Iceberg for data management and access; and cloud and on-prem HPC resources

What You'll Bring

• Education & Experience: BS, MS, or PhD in Computer Science or a related technical discipline, or equivalent experience. 8+ years of hands-on coding experience in scripting (Python, PHP, Ruby) and systems languages (Rust, C++, C#, Go, Java, or Scala).
• Data Platform Expertise: Proficiency in managing large-scale data operations, including designing scalable pipelines (streaming and batch), working with varied data types, and optimizing flexible storage solutions using tools like Argo Workflows, Databricks, Slurm, etc.
• Data Management and Development Operations: Experience with data governance, metadata, and data lineage tooling like Open Lineage or Marquez. Deep experience working with building CI/CD pipelines for data infrastructure and associated observability and monitoring tooling such as Prometheus, Grafana, OpenTelemetry, Prometheus, or Honeycomb
• Supporting Complex Data and AI ML Workflows: Experience with addressing end to end data needs for working with complex data and delivering this data ready form model training, working directly with AI Researchers and AI Engineers as part of AI model training project teams. Knowledge of data pipelines that feed Deep Learning model training that makes use of accelerated computing systems (GPUs as well as ASICs, FPGAs, TPUs)
• Containerization: Extensive experience with scaling containerized applications on Kubernetes or Mesos, with a focus on secure custom containers, replicability and portability.
• Cloud & Infrastructure: Strong experience with AWS, GCP, or Azure. Exposure to hybrid environments with on-prem and colocation systems is a plus. Familiarity with Infrastructure as Code (e.g., Terraform, Ansible) and monitoring tools (Datadog, Prometheus).
• Collaboration & Problem Solving: Proven ability to work with diverse, cross-functional stakeholders and teams to navigate complex technical challenges, adapt to evolving requirements, and drive impactful solutions.

Compensation

The Redwood City, CA base pay range for a new hire in this role is $214,000 - $295,000. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

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

Better Together

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

Benefits for the Whole You 

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

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

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

#LI-Hybrid 

The Team

Our decoding inflammation team builds tools to enable precise molecular-level measurements of inflammation within human tissues in real time, and develop proactive, early interventions that can be deployed when inflammation — which underlies the most significant causes of death worldwide — first flares in the body. You can learn more about our work here. 

Our team collaborates with three powerhouse universities - Northwestern University, the University of Chicago, and the University of Illinois Urbana-Champaign - to develop first-in-class technologies and make breakthroughs.

Our Vision

• Pursue large scientific challenges that cannot be pursued in conventional environments
• Enable individual investigators to pursue their riskiest and most innovative ideas
• Facilitate research by scientists and clinicians at our home institutions and beyond

We are a team of passionate individuals powered by technology, guided by scientific research, and driven by collaboration, working toward a mission to cure or prevent all disease.

The Opportunity

Biohub is seeking a Computational Biologist to join our interdisciplinary AI/ML team within the Virtual Immune System initiative. This is a hands-on research role focused on building and evaluating lab-in-the-loop experimental systems and closing the cycle between computational models of immune cell behavior and wet-lab validation. The ideal candidate brings strong biological intuition, computational rigor, and experience applying machine learning to genomics or perturbation biology.

You will work at the intersection of foundation models, reasoning systems, and experimental immunology — developing frameworks for how these tools can be integrated into experimental workflows. This means defining what questions are addressable, designing experiments that stress-test model predictions, guiding analysis, and evaluating performance across the loop. The environment is highly collaborative and interdisciplinary, spanning immunology, automation engineering, and machine learning, with direct applications to human health and disease.

What You'll Do

• Design computationally-guided experiments leveraging reasoning models, foundation models, and automated lab infrastructure to address open questions in immunology and inflammation.
• Partner with experimental scientists, automation engineers, and AI/ML researchers to define addressable biological questions, close the loop between model predictions and wet-lab validation, and iterate on experimental strategy.
• Develop and document best practices for designing experimental workflows, including data acquisition strategy, analysis pipelines, and frameworks for iterative refinement across the loop.
• Critically evaluate model predictions by stress-testing outputs against external datasets, known biology, and expert intuition — identifying failure modes and feeding improvements back into model development.
• Contribute to publications, open-source tools, and translational applications that advance the field of computationally driven immune system modeling.

What You'll Bring

• PhD in Immunology, Computer Science/Statistics, Computational Biology/Genomics, or a related field.
• 3 to 5 years of experience of applying machine learning and computational approaches to biological problems, particularly in genomics or genetic perturbation screening (e.g., CRISPR-based screens, Perturb-seq).
• Hands-on experience with foundation models, LLMs, or reasoning models and a drive to rigorously evaluate where they do and don't work when applied to biological questions.
• Strong biological intuition and a clear scientific point of view — able to identify which questions are tractable, design experiments that test model predictions, and know when results don't pass the smell test.
• Strong programming and data skills (Python preferred), with an emphasis on reproducibility and clear documentation.
• Effective cross-domain communicator with experience working alongside experimentalists, engineers, or other non-computational collaborators to translate between domains and validate computational predictions.

Compensation

The Chicago, IL base pay range for a new hire in this role is $162,000.00 - $202,000.00. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

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

Benefits for the Whole You 

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

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

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

#LI-Onsite