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Senior ML Research Scientist

Rad AISan Francisco - OnsiteML & Data
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Salary
$170K - $220K USD
Job type
Full-time
Posted
27 Aug 2026
Status
Open · checked 7d ago

About this role

The Senior ML Research Scientist at Radiology AI Platform for Reporting & Follow is an onsite role based in San Francisco, perfect for an experienced machine learning professional looking to transform healthcare delivery. This position suits individuals with a strong background in applied artificial intelligence who want to build production-ready systems that directly impact patient care and reduce physician burnout.

Role Overview

The Senior ML Research Scientist takes complete ownership of multimodal machine learning work-streams, guiding initiatives from initial problem definition through experimentation, evaluation, production deployment, and post-launch iteration. This position translates clinical and product requirements into actionable machine learning objectives, robust data strategies, and appropriate model architectures. The scientist designs rigorous clinical evaluations, partners closely with engineering teams to productionize models, investigates failure modes like bias or domain shift, and mentors less experienced team members.

Key Responsibilities

Own multimodal machine learning work-streams across the entire project lifecycle from ideation to production delivery.
Translate clinical and product requirements into clear modeling objectives, data approaches, and success criteria.
Build and evaluate modern machine learning architectures including transformers, self-supervised learning, detection, localization, and segmentation.
Design rigorous evaluations focused on clinically meaningful operating points, calibration, robustness, and performance across data slices.
Collaborate with engineering teams to productionize models and analyze post-launch system performance.
Investigate and mitigate failure modes such as laterality errors, hallucinations, dataset bias, and domain shift.
Contribute to the broader research roadmap and mentor junior researchers and engineers.

Requirements

Strong applied background in computer vision, natural language processing, or deep learning with a history of turning research findings into working systems.
Experience owning substantial machine learning projects from data sourcing and modeling through production.
Deep hands-on proficiency in Python and PyTorch.
Experience utilizing modern vision or multimodal techniques such as vision transformers, contrastive learning, masked image modeling, or weak supervision.
Ability to connect model performance to real user and clinical outcomes.
Strong collaboration skills across multi-disciplinary research, engineering, product, data, and clinical teams.
Clear written and verbal communication skills tailored to both technical and clinical stakeholders.
Typically requires 4+ years of relevant applied machine learning research or engineering experience, or equivalent scope and impact.
An MS, PhD, or equivalent practical experience in Computer Science, Electrical Engineering, Machine Learning, Biomedical Engineering, or a quantitative field.

Nice to Have

Experience working with medical imaging, radiology, healthcare, or high-stakes application areas.
Familiarity with chest X-ray, CT, MRI, mammography, or other clinical imaging modalities.
Experience handling DICOM data, image-report pairing, medical data de-identification, radiology workflows, or clinically derived labels.
Experience evaluating models across patients, sites, scanner vendors, protocols, or distribution shift sources.
Familiarity with clinical validation, FDA, HIPAA, or other regulated and privacy-sensitive environments.
Experience with 3D vision, longitudinal imaging, report generation, or clinical decision support.
Published research papers or open-source contributions.

Skills and Tools

Python
PyTorch
Natural Language Processing (NLP)
Computer Vision
Machine Learning Model Deployment

Salary and Benefits

Annual Salary: $170,000 to $220,000 USD
Comprehensive medical, dental, vision, and life insurance
Health Savings Account (HSA) with employer match, Flexible Spending Account (FSA), and Dependent Care FSA
401(k) retirement plan
11 paid company holidays
Flexible paid time off (PTO) policy
Annual company-wide offsite and periodic team offsites
Annual equipment stipend

About the Company

Radiology AI Platform for Reporting & Follow is on a mission to transform healthcare using artificial intelligence, saving time, reducing burnout, and improving patient outcomes. Founded by a radiologist, the organization features one of the largest proprietary radiology report datasets globally, helping uncover hundreds of new cancer diagnoses and cutting error rates in tens of millions of reports. Backed by over $140M in funding—including an oversubscribed $68M Series C round led by Transformation Capital—the company values transparency, inclusion, and close collaboration among its remote-first and onsite teams.

How to Apply

Candidates should apply directly on the official company careers page and remain vigilant against potential job scams by ensuring correspondence originates from authorized domains.

Skills and tech stack

Questions candidates ask

What is the salary range for the Senior ML Research Scientist role?

The annual salary ranges from $170,000 to $220,000 USD.

Where is this job located?

This role is based onsite in San Francisco, with an expectation to work from the office four days per week.

What level of experience is required?

The position typically requires 4+ years of relevant applied machine learning research or engineering experience, or equivalent scope and impact.

What technical skills are necessary for this position?

Candidates need strong hands-on proficiency in Python and PyTorch, alongside applied experience in computer vision, NLP, or deep learning.

What benefits does the company offer for US-based full-time roles?

Benefits include comprehensive medical, dental, vision, and life insurance, an HSA with employer match, a 401(k) plan, flexible PTO, 11 paid holidays, team offsites, and an annual equipment stipend.

Ready to apply?

The application is on the official Rad AI careers page.

Apply on company site