Staff Data Engineer

About Rad 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%. 

We have raised $50+ million to date from venture funds such as 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 have been recognized across both tech and radiology industries for being one of the most promising healthcare AI companies, including:

• CB Insights “Digital Health 50” (2023)

• CB Insights “AI 100” (2022)

• CB Insights “Digital Health 150” (2021)

• Aunt Minnie “Best New Radiology Software” (2023)

• Aunt Minnie “Best New Radiology Vendor” (2021)

Come join us in transforming healthcare with AI!

Why Join Us:

We are seeking a Staff Data Engineer to join our engineering team. Given our large client growth and projected movement in the year ahead, we're seeking to expand this team and add a strong resource on board who will play an instrumental role in the construction and maintenance of data collection systems, pipelines and management tools. This includes supervising both the functions of junior data engineers and the architectures themselves. This person would provide authority over the construction and continued operation of the Rad AI data systems. This position will report into our Director of Machine Learning and work alongside all critical parts of our business.

What You'll Be Doing:

• Design and implement the data architecture, ensuring scalability, flexibility, and efficiency using pipeline authoring tools like Metaflow and large-scale data processing technologies like Spark

• Define and extend our internal standards for style, maintenance, and best practices for a high-scale data platform

• 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 for all on your team to help them grow in their technical responsibilities. Support team members with the shipping of new features by setting direction and providing guidance

• 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

Who We’re Looking For:

• 6+ years relevant experience in data engineering 

• Expertise in designing and developing distributed data pipelines using big data technologies on large scale data sets

• Deep and hands-on experience designing, planning, productionizing, maintaining and documenting reliable and scalable data infrastructure and data products in complex environments

• Solid experience with big data processing and analytics on AWS, using services such as Amazon EMR and AWS Batch

• Experience in large scale data processing technologies such as Spark

• Expertise in orchestrating machine learning workflows using tools like Metaflow

• Experience with various database technologies including SQL, NoSQL databases (e.g., AWS DynamoDB, ElasticSearch, Postgresql)

• Prior Software Engineering experience is a big plus

Nice to Haves:

• Experience working at an early stage startup 

• Experience in a HIPAA compliant environment 

• Experience working on machine learning or healthcare related projects 

Come join our world-class team as we build and deploy AI solutions that will make a difference in millions of people’s lives. Our team is mission-driven and focused on transparency, inclusion, close collaboration, and building an inc