Senior Machine Learning Software Engineer IV

SENIOR MACHINE LEARNING SOFTWARE ENGINEER IV

Trilliant Health

About Trilliant Health

At Trilliant Health, we help hospitals and healthcare systems make smarter, data-driven decisions in an increasingly complex healthcare environment.

Our teams combine healthcare data, analytics, machine learning, and AI to build products that help healthcare leaders understand what is happening in their markets—and act with confidence.

About the Role

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

This is a senior individual contributor role with significant technical leadership responsibility . You’ll work hands-on to build production-quality software, data pipelines, tooling, and applications while helping shape the technical direction of our ML engineering organization.

You will partner closely with software engineers, ML engineers, product leaders, and other cross-functional teams to turn ideas and product strategy into well-designed, maintainable software.

The strongest candidates will be hands-on engineers who can take ownership of ambiguous, technically challenging problems; make sound engineering decisions; communicate their thinking clearly; and influence others without relying on formal authority.

You will also be expected to speak up, challenge assumptions, contribute to technical direction, and help raise the engineering capabilities of the team .

This is not a traditional data science or research role. We are looking for a software engineer who enjoys building the systems that make machine learning products possible .

Our Technology

Our engineering environment is Python-first and designed for modern data and ML development.

Python managed with uv in a monorepo

Kubernetes for running production jobs and workloads

DuckDB and Parquet for high-performance data processing

Spark and Databricks for portions of our existing data pipelines

scikit-learn, XGBoost, and PyTorch for machine learning

LangChain for newer LLM-based systems

FastAPI and NiceGUI for services and internal web applications

SQLite for several applications and tools

Azure for cloud infrastructure and deployment

GitHub and modern CI/CD practices for development and deployment

Automated testing, static type checking, and pre-commit validation

Open-source Python libraries published through PyPI and GitHub

What We're Looking For

Engineering Experience

8+ years of professional software engineering experience

Strong track record of building and maintaining production-quality software

Demonstrated ownership of significant technical initiatives from concept through delivery

Experience making architectural and technical decisions in complex software environments

Experience working effectively across engineering, product, data, and/or ML teams

Demonstrated ability to operate independently in ambiguous or evolving environments

Bachelor's, Master's, or PhD in Computer Science, Engineering, Mathematics, or a related field—or equivalent professional experience

Technical Skills

Strong, hands-on Python development experience

Experience designing and maintaining data pipelines and distributed data-processing systems

Strong understanding of software engineering fundamentals, including testing, code quality, maintainability, and performance

Experience with SQL and relational databases

Experience with CI/CD, Python packaging, and software deployment

Strong proficiency with Git and modern version-control practices

Strong familiarity with Linux and command-line tools

Experience configuring and managing development environments

Ability to design clean, reusable, well-tested, and maintainable software

Experience using AI-powered coding assistants or coding agents as part of your day-to-day development workflow

Ability to review, test, debug, and take ownership of AI-generated code rather than treating generated code as production-ready by default

Technical Leadership & Collaboration

We are looking for someone who can have an impact beyond their individual contributions.

You should be able to:

Lead significant technical initiatives without formal management authority

Influence architecture and engineering practices across the team

Speak up and constructively challenge ideas when you see a better technical approach

Clearly explain complex technical concepts to both technical and non-technical audiences

Make decisions in ambiguous situations and communicate the reasoning behind them

Work effectively with engineers, ML practitioners, product leaders, and other stakeholders

Provide mentorship and technical guidance to less-experienced engineers

Balance technical excellence with practical product and business considerations

Nice to Have

Experience building or supporting machine learning systems in production

Experience working with healthcare, healthcare data, or other complex regulated datasets

Understanding of statistics and experimental design

Experience with Spark, Databricks, or other distributed computing frameworks

Experience with Kubernetes and cloud-based production environments

Experience developing APIs or internal web applications

Contributions to open-source software

Experience working with LLMs, RAG systems, or other AI-powered applications

If you don’t meet every requirement, we’d still love to hear from you.

Why Join Trilliant Health?

You’ll have the opportunity to work at the intersection of healthcare, data, software engineering, machine learning, and AI —building technology that helps healthcare organizations make better decisions.

You’ll have meaningful ownership of challenging technical problems and the opportunity to influence how our ML engineering organization builds and scales its software.

You’ll work with a highly talented team that values:

Curiosity — asking questions and continuously learning

Ownership — taking responsibility for outcomes

Deep listening — understanding the problem before jumping to a solution

Effective communication — making complex ideas clear

Pragmatism — favoring simple, effective solutions

Collaboration — making the team better, not just the indi