Staff ML Engineer

Machinify

13h•$180,000 - $250,000•Remote

About The Position

Machinify is a healthcare intelligence company serving health plans with an AI-powered platform and expertise across the payment continuum. As a Staff ML Engineer, you will lead the design and development of large-scale systems that bring AI into production for Payment Integrity and Audit solutions. The role focuses on document processing and agentic workflows for healthcare claims, while advancing Machinify’s agentic ecosystem and delivering reliable, scalable, explainable AI systems. You will work across Data Science, Data Engineering, and Product teams to automate complex workflows, address infrastructure needs, reduce technical debt, and strengthen system reliability and scalability. You will also mentor engineers and help establish technical direction and best practices for production-grade AI systems. The role is digital-first and may be performed from anywhere in the United States. The stated base salary range is $180,000–$250,000+ depending on assessed level and candidate factors. Compensation also includes meaningful equity and benefits.

Requirements

Deep software engineering experience, including meaningful experience building agentic systems or AI-driven workflows in an enterprise setting.
Strong programming expertise in Java and Python.
Experience designing and scaling large-scale distributed systems and pipelines, ideally processing unstructured data such as documents or healthcare records.
Proven ability to productionize AI/ML techniques such as LLM prompt engineering, RAG, workflow automation, and agents, with attention to reliability, observability, and explainability.
Knowledge of monitoring and observability tools such as Prometheus, Grafana, or similar, and an interest in tracking metrics.
Strong computer science fundamentals, including data structures, asynchronous programming, and system design.
Demonstrated success reducing manual processes through automation.
Collaborative experience working with data scientists and cross-functional teams to translate requirements into technical designs and production systems.
Bachelor’s or Master’s degree in Computer Science or a related field, or equivalent practical experience.
Track record of building and shipping enterprise-grade AI/ML systems in production.
Strong testing and code quality discipline, with experience contributing to and improving enterprise-grade systems.

Nice To Haves

Experience with Scala.
Experience in healthcare, fintech, or another regulated domain.
Experience with big-data tools and distributed systems frameworks such as Spark, Flink, Kafka, Airflow, or Ray.

Responsibilities

Lead development of document processing pipelines capable of handling hundreds of millions of documents annually, including medical records, claims, and benefits data.
Design and implement agentic workflows to review and validate millions of healthcare claims per year, ensuring accuracy and payment integrity.
Advance the agentic ecosystem through prompt development lifecycle improvements, use of multimodal text and vision LLMs, context extraction, RAG, workflow orchestration, observability and logging, and explainability of LLM outputs.
Collaborate with Data Science, Data Engineering, and Product teams to deliver robust, end-to-end AI-powered systems that automate complex workflows.
Track and reduce technical debt while strengthening system reliability and scalability.
Mentor and guide engineers on best practices for production-grade AI systems and help set technical direction for the team.