Rad AI - Research Scientist, Machine Learning

Salary: $170K - $220K Employment Type: Full-Time Location Type: Remote

About Rad AI

Rad AI is on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI-driven solutions are revolutionizing radiology—saving time, reducing burnout, and improving patient care. With one of the largest proprietary radiology report datasets in the world, our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%.

Rad AI has secured over $140M in funding, including a recently oversubscribed Series C ($68M round) led by Transformation Capital, bringing our valuation to $528M. Our investors include Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and others—all backing our mission to empower physicians with cutting-edge AI.

Our latest advancements in generative AI are used by thousands of radiologists daily, supporting more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.

Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie, and ranked by Deloitte as the 19th fastest-growing company in North America, we are building AI-powered solutions that make a real impact. Most recently, Rad AI was named to CNBC’s Disruptor 50 list, highlighting the innovation and momentum behind our mission.

If you’re ready to shape the future of healthcare, we’d love to have you on our team!

Why Join Us?

We’re on a mission to build cutting-edge AI systems that empower radiologists and improve patient care. As a Research Scientist on our Machine Learning team, you’ll work at the intersection of speech modeling, machine learning, and healthcare, interfacing with our partners to design and deploy state-of-the-art ASR and speech-based models that solve real-world healthcare challenges. This is a high-impact role where your work will directly influence clinical workflows and improve physician efficiency at scale.

What You’ll Do

• Develop advanced speech processing pipelines and quality assurance systems for medical dictation workflows.
• Research offline speech processing capabilities and edge computing solutions for clinical environments.
• Tackle complex challenges unique to healthcare and radiology, such as converting dictated speech into structured data, enabling real-time clinical decision support, or building voice interfaces.
• Work closely with vendor relationships to enhance integration and performance metrics.
• Drive Applied Research: Stay current with cutting-edge research in speech and audio ML, design experiments, and prototype ideas that can be translated into production.

What We’re Looking For

• MS or PhD in Computer Science, Electrical Engineering, Machine Learning, or a related field, or equivalent practical experience.
• 2+ years of post-degree experience building models in ML Speech technologies such as Automated Speech Recognition/Speech-to-Text (ASR/STT), or Text-to-Speech (TTS).
• Strong experience working with transformer-based speech models such as Whisper.
• Proficiency with Python and deep learning frameworks like PyTorch.
• Familiarity with open-source libraries such as ESPnet, HuggingFace Transformers, torchaudio, or Kaldi.
• Experience deploying speech or audio models in production settings.
• Experience working with and curating large audio datasets.

Bonus Points For:

• PhD, or research background in speech ML, signal processing, or voice-based interfaces.
• Experience working in healthcare, regulated environments, or HIPAA-compliant systems.
• Publications in top-tier ML or speech-specific conferences (e.g., INTERSPEECH, ICASSP, NeurIPS).
• Experience working in early-stage startups or fast-paced R&D teams.
• Familiarity with cloud platforms (AWS, GCP) and modern ML ops toolchains.

Join our world-class team as we build and deploy AI solutions.