ML Engineer

Press Ganey

. Build, test, and deploy production-ready AI agents and agentic workflows integrated with enterprise applications and business processes .

Posted 9/23/2026full-timeRemote • United StatesJuniorMid-Level💰 $110,000 - $130,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying AI agents and workflows, with a strong foundation in machine learning model optimization and integration within enterprise applications. Proficient in collaborating with cross-functional teams to deliver reliable software solutions and implement safety frameworks for AI applications.

Highest-signal resume keywords

Machine Learning EngineeringProduction-Grade LLM ApplicationsPython DevelopmentAI-Enabled ApplicationsCI/CD and Automated Testing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningModel OptimizationData StructuresAlgorithm DesignObject-Oriented DesignPythonJavaPyTorchTensorFlowRetrieval-Augmented Generation

Soft Skills

CommunicationCollaboration

Tools & Technologies

LangChainLangGraphSpring AIAWSAzureGCPKubernetesDatabricksSpring BootContainerized Deployments

Industry Keywords

AI AgentsEnterprise ApplicationsMicroservicesObservabilityPerformance Optimization

Tech Stack

Tools & technologies

AWSAzureDistributed SystemsGoogle Cloud PlatformJavaKubernetesMicroservicesPythonPyTorchSpringSpring BootSpringBootTensorflow

About the role

Key responsibilities & impact

Build, test, and deploy production-ready AI agents and agentic workflows integrated with enterprise applications and business processes
Implement evaluation, monitoring, guardrail, and safety frameworks for LLM-powered applications
Develop and maintain AI-enabled features within the Java/Spring platform and distributed microservices ecosystem
Collaborate with AI Scientists and ML Engineers to productionize models and translate experimentation into reliable software
Stay current with emerging AI technologies and recommend pragmatic adoption strategies
Incorporate feedback from specialists, tech-ops, and product managers
Participate in design reviews, technical discussions, and requirement planning
Attend daily stand-up meetings, collaborate with peers, prioritize features, and deliver customer value
Prototype and test potential solutions to large problems

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience
2–5 years of hands-on experience as a Machine Learning Engineer
Proven track record designing, building, and optimizing ML models using PyTorch or TensorFlow for production environments
Solid Computer Science fundamentals in data structures, algorithm design, complexity analysis, and performance optimization
Strong proficiency in object-oriented design and development using Python, Java, or C#
Hands-on experience developing, testing, and supporting applied machine learning services within enterprise software ecosystems
Practical experience building and maintaining software components for AI-enabled applications or distributed systems
Hands-on experience integrating AI capabilities into existing enterprise applications
Experience implementing and deploying production-grade LLM applications using LangChain, LangGraph, Spring AI, Model Context Protocol (MCP), or similar technologies
Solid working knowledge of Retrieval-Augmented Generation (RAG), tool calling, prompt engineering, and core AI agent principles
Experience in observability, CI/CD, automated testing, and production operations for AI applications
Excellent communication and collaboration skills
Preferred: Experience with Databricks, vector search technologies, embedding models, conversational AI, evaluation strategies for AI agents, AI developer tooling, large-scale Java microservices using Spring Boot, AWS/Azure/GCP, Kubernetes, containerized deployments, model serving, inference optimization, caching strategies, and cost optimization

Benefits

Comp & perks

Competitive benefits package
Discretionary bonus or commission tied to achieved results
Reasonable accommodations for qualified individuals with disabilities or disabled veterans in the hiring process