Machine Learning Research Jobs in San Francisco, CA

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Description:

Who we are:

The Gladstone Institutes is a leading independent, not-for-profit research organization dedicated to improving human health through groundbreaking biomedical research and education. Our work spans neuroscience, cardiovascular biology, immunology, and stem cell biology, with a strong emphasis on understanding and treating disease. With approximately 600 team members, including world-renowned scientists and biomedical leaders, Gladstone fosters a collaborative and innovative environment. Located in Mission Bay in a state-of-the-art facility, we offer competitive salaries, comprehensive benefits, and the resources to empower individuals to maximize their potential and make a meaningful impact on global health.

About the Role:

The Finkbeiner Lab at Gladstone Institutes is seeking a ML Research Engineer to join a team of computer scientists applying AI/ML in diverse biomedical research projects. This involves working closely with biologists, imaging scientists, and engineers to accelerate the lab's computational efforts, developing, adapting, and translating cutting-edge machine learning methods into tools that meaningfully speed up discovery in neurodegeneration and other disease areas.

This is a highly collaborative position for someone who wants their ML work to directly shape how biological experiments are designed and run, advance neurodegenerative disease research by uncovering meaningful correlations across pathology datasets, and help lab members improve and scale cell image analysis pipelines. The role will also contribute to advancing our “thinking microscope” — an intelligent live-cell imaging platform that uses closed-loop machine learning to autonomously guide experiments and accelerate scientific discovery.

What you will do:

• Deploy Computer Vision and RL Pipelines : Design, implement, and deploy computer vision approaches and reinforcement learning pipelines for high-content cellular imaging data, including adaptive acquisition strategies for automated microscopy.

• Train & Fine-Tune Models : Train, fine-tune, and benchmark multimodal models for pathology, cell segmentation across large longitudinal imaging, sequencing datasets, and evaluate performance against biologically meaningful metrics.

• Accelerate Computational Research : Partner with lab members to streamline AI/ML workflows, improve data processing efficiency, and resolve complex computational bottlenecks in ongoing experiments.

• Drive Collaborative & Grant Initiatives : Partner with internal and external collaborators, contribute to manuscripts and presentations, and help lead grant writing efforts by developing the computational aims, preliminary data, and methods narratives that drive successful proposals.

• Demystify AI for Biology: Translate complex computational concepts into clear, actionable insights for non-technical team members and interdisciplinary collaborators.

What you will need:

• Education & Experience : Requires Bachelor’s degree in engineering, computer science, physics or related field. 4+ years of related experience for individuals with a BS/BA or 2+ years of related experience for individuals with a MS degree

• Frameworks, Infrastructure & Scaling: Hands-on experience with deep learning tools (PyTorch, JAX, OpenCV, Hugging Face), MLOps frameworks (Docker, containerization, Computer Systems) and distributed platforms (Slurm, Kubernetes) and software engineering practices

• Domain Expertise: Practical experience applying machine learning, deep learning, computer vision, transformer architectures, and reinforcement learning.

• Interdisciplinary Drive and Leadership Skills : Genuine curiosity for biological discovery and a strong motivation to apply AI to solve complex biological problems, and a willingness and capacity to seek out new emerging solutions from across computer science.

• Communication & Teamwork : Proven ability to explain technical ML concepts to non-technical stakeholders, with a collaborative, team-first mindset.

What is preferred:

• Prior experience with biological or biomedical image analysis, including microscopy data, cell segmentation, or object tracking

• Experience applying reinforcement learning to real-world control problems, particularly closed-loop or instrument-in-the-loop systems

• Hands-on experience with distributed training, fine-tuning, or deploying large-scale vision or multimodal foundational models

Salary Range:

$88K - $120K

Gladstone Perks & Benefits

• People –work with talented, committed, and supportive teammates within an organization that values each member of its community.

• A meaningful place to grow and learn –whether it’s your professional skills or scientific knowledge, we have the resources and environment to advance either so you can better support Gladstone’s mission to drive a new era of discovery in disease-oriented science and to mentor tomorrow’s leaders in an inspiring and excellent environment.

• Healthy work/life balance –you are highly engaged and productive at work because you can have time to recharge and enjoy a vibrant life outside of work.

• Compensation –competitive salary. Title and salary will be commensurate with education and experience.

• Excellent benefits –generous medical, dental, vision, retirement plan, paid vacation, commuter benefits, access to free shuttle transportation.
  
  

Gladstone is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, sex, religion, national origin, ancestry, age, marital status, medical condition, physical or mental disability, veteran status, sexual orientation, or any other non-job related characteristic. We make all employment decisions so as to further this principle of equal employment.