Senior Machine Learning Research Scientist - MLOps

Senior Machine Learning Research Scientist - MLOps

Remote (United States)

SmarterDx, a Smarter Technologies company, builds clinical AI that is transforming how hospitals translate care into payment. Founded by physicians in 2020, our platform connects clinical context with revenue intelligence, helping health systems recover millions in missed revenue, improve quality scores, and appeal every denial. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com / careers.

Role

As a Senior Machine Learning Research Scientist, you will lead groundbreaking ML research and development at SmarterDx, collaborating closely with experienced engineers and clinicians to turn your inventions into enterprise‑grade products. With minimal supervision, you will establish a research agenda informed by emerging trends in AI, develop and rigorously evaluate your proposed algorithms, deploy your algorithms into production, and monitor impact. You will collaborate closely with other machine learning research scientists to identify the most promising areas of AI / ML R&D for SmarterDx and establish shared infrastructure to accelerate research efforts across the team.

What You'll Do

• Invent and deploy state‑of‑the‑art machine learning algorithms
• Share insights and breakthroughs through publications in top‑tier conferences, journals, blog posts, and other mediums to showcase your work
• Survey and share relevant AI / ML research and emerging technologies within the company to help others stay abreast of important trends
• Establish and own an ambitious research agenda with regular milestones
• Frequently present your work internally and solicit feedback from other machine learning research scientists, data scientists, engineers, and clinicians
• Provide constructive feedback to other ML research scientists on the team
• Collaborate cross‑functionally with clinical, engineering, and product teams to understand key needs and prioritize research accordingly
• Work in a fast‑paced and rewarding environment that demands high quality work with minimal supervision
• Collaborate cross‑functionally with engineering to assist in configuring the correct infrastructure for training and inference
• Collaborate cross‑functionally with engineering, data engineering, data analytics and data science to evaluate models in production, troubleshoot and update models based on real world results

What You Bring

Nice To Haves

Compensation

$200‑220k base salary + equity incentives

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