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# Senior Machine Learning Engineer

- **Company:** Trilliant Health
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Automation of Tests, Microsoft Azure, Big Data, Command-Line Interface, Continuous Integration, Relational Databases, Linux, Distributed Data Store, Github, Python (Programming Language), Machine Learning, Open Source Technology, Software Deployment, Software Engineering, SQLite, SQL Databases, Web Applications, Parquet, Pytorch, Large Language Models, Apache Spark, Model Validation, Generative AI, AI Coding Agents, Git, Fastapi, Scikit Learn, Kubernetes, Information Technology, Code Testing, Xgboost, Free and Open-Source Software, Machine Learning Operations, Entity Resolution, Software Version Control, Databricks
- **Published:** October 12, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=0ee1d70563a4b907

## About the Role

* 8+ years of professional experience in machine learning, software engineering, data science, or a closely related technical discipline, with significant hands-on experience building production ML systems
 * Bachelor's, Master's, or PhD in Computer Science, Engineering, Mathematics, Statistics, or a related field or equivalent professional experience
 * Demonstrated experience taking ownership of significant ML initiatives and influencing technical decisions across teams
 * Demonstrated willingness to speak up, challenge assumptions, and advocate for sound technical or modeling decisions.
 * Experience working collaboratively across engineering and cross-functional teams

Machine Learning & Data Science

 * Strong understanding of predictive modeling and machine learning techniques
 * Experience selecting, developing, evaluating, and improving ML models
 * Understanding of statistics, experimentation, and model evaluation
 * Experience working with large, complex datasets
 * Experience developing ML workflows from experimentation through production

Software Engineering

 * Strong, hands-on Python development experience, including writing production-quality, maintainable, and well-tested code
 * Experience developing and maintaining distributed data pipelines
 * Experience with SQL and relational databases
 * Experience with CI/CD, Python packaging, and software deployment
 * Proficiency with Git and modern version-control practices
 * Strong familiarity with Linux and command-line tools
 * Ability to write clean, reusable, maintainable, and well-tested code
 * Experience using AI coding agents and reviewing, testing, and improving agent-generated code

Nice to Have

 * Experience building, evaluating, or deploying LLM-based or other AI systems
 * Experience with Healthcare claims data
 * Experience with entity resolution/record linkage
 * Experience with Spark or similar compute frameworks
 * Open-source contributions

## Description

We are seeking a Senior Machine Learning Engineer IV to join our Machine Learning (ML) team and help build the models, systems, and software that power Trilliant Health's machine learning and AI capabilities.

This is a senior individual contributor role combining hands-on machine learning, software engineering, and technical leadership. You'll work with complex healthcare data to develop production-ready ML solutions and help shape the technical direction of our ML engineering organization.

We value engineers who are curious, proactive, collaborative, and able to communicate complex technical concepts clearly to both technical and non-technical audiences. We prefer simple solutions over complex ones, and we document what we build and how it works.

Our Stack

Our stack is built around Python, which we manage with uv in a monorepo. Most of our heavy computation runs as jobs on Kubernetes, where we increasingly favor DuckDB and Parquet, though some of our pipelines still run on Spark and Databricks.

We build our models with libraries including scikit-learn, XGBoost, and PyTorch, and our newer LLM-based systems with LangChain. Our services and internal web applications use FastAPI and NiceGUI, several of them backed by SQLite, and we deploy everything to Azure.

Every change runs through pre-commit hooks, static type checking, and automated tests before it merges. We also publish several of our core libraries as open source on PyPI and GitHub.