Staff Research Engineer, AI Engineering

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.

The Team

Biohub supports the science and technology that will make it possible to help scientists cure prevent or manage all diseases by the end of this century. While this may seem like an audacious goal in the last 100 years biomedical science has made tremendous strides in understanding biological systems advancing human health and treating diseour organization and research partners all for the purpose of contributing to greater understanding of human cell function.

You will have the opportunity to work closely with teams of scientists computational biologists engineers and to collaborate with our grantees with our institutes and other external labs and organizations. Your work will inspire and enhance the production and analysis of datasets by teams and collaborators. Scientific focus areas could include single cell biology imaging genomics and proteomics.

What Youll Do

• Working with the AI Research Scientists iterate on optimize deploy and maintain innovative machine learning models systems and software tools that enable the analysis and interpretation of AI models for Biology
• Work with cross-functional team members to quickly iterate on system performance to meet/stay ahead of users needs - e.g. we get feedback that the model doesnt scale to X million so working with our user researcher/scientist/product team to iterate on the solution.
• Partner with research scientists to build robust data loader pipelines for scalable distributed training and evaluation.
• Serve as an interface to product and engineering teams to understand how models may need to evolve to support multiple use cases.
• Develop model evaluation and interpretability frameworks that help biologists understand which data features drive model predictions
• Build reusable engineering utilities that can unlock experimentation velocity across research initiatives in the organization
• Optimize model architectures to enhance performance fine-tune accuracy and efficiently manage infrastructure resources

What Youll Bring

• Experience in working with a highly interactive and cross-functional collaborative environment with a diverse team of colleagues and partners solving complex problems through applied deep learning.
• A track record and expertise in developing deep learning models on large-scale GPU clusters using techniques of distributing training such as DDP FSDP Model parallelism low-precision training profiling and optimizing AI/ML code fine tuning models.
• Expertise in leading end-to-end experimentation pipelines for training and evaluating deep learning models with particular focus on experiment tracking and reproducibility.
• A good working knowledge of Python-based ML libraries and frameworks such as PyTorch JAX TensorFlow NumPy Pandas and Scikit-learn.
• Experience in using modern frameworks for distributed computing and infrastructure management particularly as related to ML models such as PyTorch Lightning Deepspeed TransformerEngine RayScale etc.
• Ability to effectively balance exploratory research with robust engineering practices.
• A good working knowledge of general software engineering practices in a production environment.
• The ability to work independently and as part of a team and have excellent communication and interpersonal skills.
• Have a Masters in computer science with a focus on machine learning & data analytics or equivalent industry experience and at least 6-8 years of experience developing and applying machine learning methods.

Compensation

The Redwood City CA base pay range for a new hire in this role is $241000 - $362000. 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.

Work Mode

As we grow were 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 teams manager. The exact schedule will be at the hiring managers discretion and communicated during the interview process.

Benefits for the Whole You

Were 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 youre interested in a role but your previous experience doesnt 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