Data Engineering Manager

About Rad AI

We have raised $80+ million to date from venture funds and just closed on our series B financing with investors Khosla Ventures, Gradient (Google’s AI fund) and ARTIS. We’ve also formed a partnership with Google to collaborate on the future of generative AI to redefine healthcare. Currently, more than 1/3 of radiology groups and healthcare systems, including Kaiser Permanente, HCA Healthcare, and Geisinger, now leverage the latest Gen AI advancements from Rad AI. We're recognized as one of the most promising healthcare AI companies by both CB Insights and AuntMinnie. Come join us in transforming healthcare with AI!

Founded by the youngest US radiologist in history, Rad AI empowers physicians with Al to save time, reduce burnout, and improve the quality of patient care. By combining our deep expertise in healthcare and AI and using one of the largest proprietary radiology report datasets in the world, our AI has uncovered hundreds of new cancer diagnoses for patients and reduced the error rate in tens of millions of radiology reports by nearly 50%. 

Why Join Us:

Comprising both radiology and AI expertise, Rad AI's stellar team builds products that maximize radiologist productivity, ultimately making healthcare more widely accessible and improving patient outcomes. Join our team and help us make a positive impact on radiology, patient lives, and healthcare around the world.

This role will lead our Data Engineering team to support our rapid client growth and projected expansion in the year ahead. In this role, you will play an instrumental part in the construction and maintenance of data collection systems, pipelines, and management tools, as well as managing the data engineering team. As the authority over the construction and continued operation of Rad AI data systems.

Responsibilities:

• Manage a team of data engineers at a variety of levels.

• Collaborate with ML engineers and researchers to understand their data needs, including model training and production monitoring systems, and develop solutions that meet those requirements.

• Provide mentorship and guidance for your team members, helping them grow in their technical responsibilities, setting direction, and ensuring timely delivery of new features.

• Ensure data quality, integrity, and security by implementing robust data validation, monitoring, and access controls.

• Evaluate and recommend data technologies and tools to improve the efficiency and effectiveness of the data engineering process.

• Continuously monitor, maintain, and improve the performance and stability of the data infrastructure.

• Determine the roadmap, direction, and …