Backend Engineer - Machine Learning Platform

The Role

As a Backend Engineer on the Machine Learning Platform team, you’ll build and maintain the core systems that power Frontera’s AI and ML capabilities—from training pipelines and model inference APIs to video processing and feature stores. You’ll design scalable, reliable pipelines for ingesting, transforming, and serving large-scale datasets used for ML training and prediction. You’ll work closely with ML scientists, data engineers, and product engineers to ensure models can be trained, deployed, and updated efficiently while supporting rapid experimentation and long-term scalability. Your work will directly enable ML-driven features that help care teams work smarter and reach more children.

Responsibilities

• Design, develop, and maintain scalable backend services and APIs, ensuring high performance, security, and reliability.
• Build and optimize data pipelines to ingest, store, and serve large-scale datasets, including video and ML training data.
• Own and evolve the foundational data model that powers the entire Frontera platform.
• Balance rapid development of MVPs and POCs for user research with building robust, long-term backend foundations.
• Integrate third-party tools and services to enhance platform functionality.
• Collaborate closely with engineers, machine learning scientists, and clinicians to align platform capabilities with user needs.

Qualifications

• 4+ years of experience as a Backend Engineer, with expertise in Python, Java, or similar languages.
• Deep understanding of API development, database design (relational and NoSQL), and building scalable data pipelines and orchestration workflows.
• Experience with cloud platforms (AWS, Azure, GCP).
• Thriving in a fast-paced, dynamic environment.

Bonus Points

• Experience with AI/ML technologies and applications in healthcare.
• Familiarity with video storage, processing, and streaming technologies.