HeartFlow
- Software Engineer, ML Engineering/ml Ops
Software Engineer, ML Engineering/ml Ops
Engineering · United States · Remote possible
Job description
HeartFlow, Inc. is a medical technology company advancing the diagnosis and management of coronary artery disease, the #1 cause of death worldwide, using cutting-edge technology. The flagship product—an AI-driven, non-invasive cardiac test supported by the ACC/AHA Chest Pain Guidelines called the HeartFlow FFRCT Analysis—provides a color-coded, 3D model of a patient’s coronary arteries indicating the impact blockages have on blood flow to the heart. HeartFlow is the first AI-driven non-invasive integrated heart care solution across the CCTA pathway that helps clinicians identify stenoses in the coronary arteries (RoadMap™Analysis), assess coronary blood flow (FFRCT Analysis), and characterize and quantify coronary atherosclerosis (Plaque Analysis). Our pipeline of products is growing and so is our team; join us in helping to revolutionize precision heartcare.
HeartFlow is a VC-backed, pre-IPO company that has received international recognition for exceptional strides in healthcare innovation, is supported by medical societies around the world, cleared for use in the US, UK, Europe, Japan and Canada, and has been used for more than 250,000 patients worldwide.
We seek a highly motivated and dynamic Software Engineer to join our Machine Learning (ML) Engineering and MLOps team. This position is ideal for an engineer passionate about building and deploying scalable ML systems. The successful candidate will work closely with our experienced engineers to design, build, and maintain the infrastructure and tools necessary for rapid ML development and deployment. You will gain hands-on experience with the latest technologies in machine learning and cloud computing, contributing to projects that impact our products and services, and ultimately, move the needle on heart disease. #LI-Remote; #LI-IB1
Required Qualifications
- Bachelor's/Masters degree in Computer Science, Engineering, Mathematics, or a related field
- 2+ years of relevant experience
- Experience developing distributed systems, big data technologies, and real-time data processing.
- Familiarity with machine learning concepts and frameworks (e.g., PyTorch, Scikit-learn).
- Strong foundation in software engineering principles and practices, with proficiency in at least one programming language (e.g., Python, C++).
- Experience with cloud services (AWS, GCP, Azure) is a plus.
- Understanding of data structures, algorithms, and software design principles.
- Basic knowledge of containerization and orchestration technologies (e.g., Docker).
- Strong problem-solving skills and the ability to work independently as well as collaboratively in a team environment.
- Excellent communication and interpersonal skills.
How You Stand Out
- Experience with continuous integration and continuous deployment (CI/CD) pipelines and familiarity with related tools (e.g., Jenkins, Github Actions).
- Experience with a container orchestration framework (e.g., Kubernetes).
- Experience with data warehouses (e.g., Redshift / Snowflake / Databricks).
- A keen interest in staying up-to-date with the latest trends and advancements in machine learning, artificial intelligence, and cloud computing.
- Demonstrated initiative and creativity in solving complex problems.
- Blog (or other media) communicating the candidate’s data science or engineering projects, ideas, or first-principles thinking.
A reasonable estimate of the base salary compensation range is $102,350 to $150,050 (for all locations outside San Francisco Bay Area) and $120,000 to $170,000 (for San Francisco Bay Area), cash bonus, and stock options.