ML Engineer II: Production AI for Enterprise Apps

Press Ganey; Washington (District of Columbia); On-site; USD 110,000 - 130,000; Full time

Job summary

Press Ganey seeks an ML Engineer II to expand and scale our AI capabilities across healthcare and enterprise apps. You will build production-ready AI agents, integrate with Java/Spring platforms, and collaborate with AI scientists to productionize models.

You'll own end-to-end software quality, implement guardrails for LLMs, and stay current with AI trends while delivering value to customers in an agile environment.

Qualifications

• Bachelors or equivalent practical experience in CS/engineering.
• 2–5 years of hands-on ML engineering experience in production.
• Proficiency in Python, Java or C# and OO design.
• Experience with PyTorch or TensorFlow in production environments.
• Experience building ML services within enterprise software.
• Experience deploying LLM apps using LangChain, LangGraph, Spring AI or MCP.
• Knowledge of Retrieval-Augmented Generation, tool-calling, and prompt engineering.
• CI/CD, observability, and production operations for AI apps.

Responsibilities

• Build, test, and deploy production-ready AI agents and workflows.
• Implement evaluation, guardrails, and safety frameworks for LLM apps.
• Develop AI-enabled features within Java/Spring microservices.
• Collaborate with AI scientists and ML engineers to productionize models.
• Stay current with AI tech and advise on pragmatic adoption.

Skills

Python

Java

C#

PyTorch

TensorFlow

Distributed systems

AI/ML engineering

CI/CD

Education

BSc in Computer Science or related field

Tools

Databricks

LangChain

LangGraph

Spring AI

Kubernetes

AWS

Spring Boot

Job description

Press Ganey seeks an ML Engineer II to expand and scale our AI capabilities across healthcare and enterprise apps. You will build production-ready AI agents, integrate with Java/Spring platforms, and collaborate with AI scientists to productionize models.

You'll own end-to-end software quality, implement guardrails for LLMs, and stay current with AI trends while delivering value to customers in an agile environment.