Senior ML Research Scientist

As a Senior ML Research Scientist at Rad AI, you will own a multimodal ML work-stream from problem definition through experimentation, evaluation, deployment, and iteration. You will translate clinical and product needs into clear ML objectives, data strategies, model approaches, and success criteria. You will build and evaluate modern ML systems, including transformers, self-supervised learning, weak supervision, detection, localization, and segmentation. You will work with image, report, and other clinical data to develop systems that are useful in real radiology workflows. You will design rigorous evaluations that go beyond aggregate offline metrics, including clinically meaningful operating points, robustness, calibration, and performance across relevant data slices.

What You Will Do

Your day-to-day responsibilities will include owning substantial ML projects across the full lifecycle, from data and modeling through production delivery. You will have the ability to go deep technically, stay close to the clinical context, and make progress even when the problem and the path are not fully defined. You will communicate research findings and technical decisions clearly through design documents, experiment reviews, and presentations to technical and clinical partners.

Why It Might Be a Fit

We are looking for a strong applied experience in computer vision, NLP, or deep learning, with a track record of independently designing experiments, analyzing results, and turning findings into working systems. You will have experience owning substantial ML projects across the full lifecycle, from data and modeling through production delivery. You will have a deep hands-on ability in Python and PyTorch, with strong intuition for model architecture, data quality, experimentation, and evaluation.

Requirements

• Strong applied experience in computer vision, NLP, or deep learning
• Experience owning substantial ML projects across the full lifecycle
• Deep hands-on ability in Python and PyTorch
• Experience with modern vision or multimodal techniques
• Ability to connect model performance to real user and clinical outcomes
• Strong collaboration skills across research, engineering, product, data, and clinical teams
• Clear written and verbal communication
• Typically 4+ years of relevant applied ML research or engineering experience

Benefits

• Comprehensive Medical, Dental, Vision & Life insurance
• HSA (with employer match), FSA, & DCFSA
• 401(k)
• 11 Paid Company Holidays
• Flexible PTO policy
• Annual company-wide offsite
• Periodic team offsites
• Annual equipment stipend