About Us

We're tackling one of healthcare's most critical challenges in medical imaging and diagnostics. Our company operates at the intersection of cutting-edge AI and clinical practice, building technology that directly impacts patient outcomes. We've assembled one of the industry's most comprehensive and diverse medical imaging datasets and have a proven product-market fit with a substantial customer pipeline already in place.

Role Overview

This is a unique opportunity for a strong generalist engineer who thrives in ambiguity, loves solving complex problems, and wants to have outsized impact. You'll work alongside our ML team to build the foundation that will scale our technology to millions of patients.

As a critical member of our lean engineering team, you'll wear multiple hats - from designing APIs and shipping production features, to building robust ML infrastructure and optimizing system performance.

Key Responsibilities

• Design, develop, test, deploy, and operate fully integrated solutions that provide seamless end-to-end experiences

• Lead technical design decisions for major product features

• Design, build, and maintain infrastructure for modern integration methods between our applications and our customers’ applications

• Collaborate extremely effectively with internal users (technical and non-technical), other engineers, stakeholders, and vendors on projects within the team and across the company to understand requirements and translate them into technical solutions.

• Communicate technical ideas and work closely with other senior members of the team

• Mentor team members and establish engineering best practices

• Take ownership of large projects from conception to deployment

• Drive architecture and code quality through rigorous testing, thoughtful design reviews, and scalable engineering practices that ensure performance, reliability, and maintainability across the stack

Some example projects that you will be working on

• Design and develop a centralized ETL, data lake, and data warehouse solution for hundred of terabytes of data

• Build and optimize ML model inference pipelines for both live traffic and offline data.

• Develop a comprehensive framework shared across ML research and product traffic to validate model performance on diverse clinical scenarios

• Design and build an experimentation framework that will allow ML scientists to quickly A/B test multiple ML models

• Design a reliable, robust cloud-based networking infrastructure that allows seamless onboarding and integration multiple (potentially infinite) external sites

Qualifications

• 5+ years of experience as a software engineer, demonstrably delivering on time, at quality

• Full stack experience with emphasis on the BE and infrastructure:

  • Experience in a backend language such as Go, Python, Java, or similar

  • Experience with cloud platforms and distributed architectures, specifically with AWS

• Have hands-on experience with schema design and data modeling

• Strong experience designing and building backend infrastructure (API, ML infrastructure, data pipeline) that is reliable, scalable and easy to maintain

• Strong problem-solving skills and the ability to troubleshoot complex systems.

• Have experience shipping things quickly with competing priorities or deadlines

• Are a team player, willing to do a variety of tasks that move the team forward

• Excellent communication skills and ability to work cross-functionally