Senior Software Engineer, Applied AI

About Us

At 3Y Health, we are building AI-driven software to empower healthcare providers and solve the overwhelming administrative complexity that consumes 40% of the industry’s revenue. Our end-to-end platform unlocks opportunities for clinician entrepreneurs, enabling medical professionals to launch, run, and grow private practices. By supporting these independent practices with the latest AI and automation, we’re helping providers reclaim their time, build thriving businesses, and deliver better outcomes for their communities. 3Y Health is backed by over $200M from top-tier investors including Founders Fund, General Catalyst, Softbank, and 8VC.

About the Role

We’re looking for a Senior Software Engineer, Applied AI—someone who thrives at the intersection of experimentation and engineering excellence. In this role, you’ll work with a wide range of AI models and services, evaluate their performance, and build the production-grade systems that bring them to life in real applications.

Responsibilities

• Run hands-on experiments with third-party and in-house AI models (e.g., LLMs, CV models, speech, etc.) to test performance, quality, and viability for real-world use cases.
• Design and implement robust, production-ready AI services that integrate ML models into user-facing applications.
• Develop and maintain pipelines for model evaluation, offline testing, and continuous integration of model updates.
• Design scalable data models and storage strategies for ML data, including features, labels, metadata, and evaluation metrics.
• Collaborate with research, product, and infrastructure teams to align model performance with business objectives and production constraints.
• Write clean, testable code in modern languages (e.g., Python, TypeScript, Go) and deploy via scalable infra (e.g., Docker, Kubernetes, serverless).

Qualifications

• 3+ years of software engineering experience, including 2+ years in ML-focused roles.
• Strong experience running and evaluating ML models (e.g., LLMs, classification, recommendation, etc.).
• Proficient in building APIs and services to serve models in production environments.
• Experience building ML pipelines for training, evaluation, and testing using tools like Airflow, MLflow, Weights & Biases, or similar.
• Solid understanding of data modeling, data storage, and data engineering fundamentals for ML use cases.
• Comfortable with versioning, benchmarking, and monitoring models in production.

Compensation 

The estimated salary range for this role is $175,000 - $205,000. Total compensation for this position may also include stock options. Note that total compensation for this position will be determined by each individual’s relevant qualifications, work experience, skills, and other factors.