ML Engineer II: Build Production AI & Safe, Scalable Agents

pressganey; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Press Ganey is seeking an ML Engineer II to expand and scale our Machine Learning and AI capabilities across business units. You will join a Java/Spring platform ecosystem, build production-ready AI agents, and collaborate with AI scientists to translate experiments into reliable software.

You will thrive by crafting clean code, owning software quality end-to-end, and staying current with AI innovations to improve product capabilities and developer productivity.

Qualifications

• 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, with proven production-model work.
• Solid CS fundamentals in data structures, algorithms, complexity analysis, and performance optimization.

Responsibilities

• Build, test, and deploy production-ready AI agents and workflows for enterprise apps.
• Implement evaluation, monitoring, guardrails, and safety frameworks for de-risking LLM-powered apps.
• Develop and maintain AI-enabled features within Java/Spring platform and microservices.
• Collaborate with AI scientists and ML engineers to productionize models.
• Stay updated with emerging AI technologies and advise on adoption strategies.
• Work with specialists, tech-ops, and product managers for feedback.
• Participate in design reviews and requirement planning to grow technical skills.
• Attend stand-ups, prioritize features, and deliver value with urgency.
• Prototype and test innovative solutions to large problems.

Skills

Machine learning experience

Education

Bachelor's in CS/Engineering or related

Tools

PyTorch

TensorFlow

Java

Spring

Job description

Press Ganey is seeking an ML Engineer II to expand and scale our Machine Learning and AI capabilities across business units. You will join a Java/Spring platform ecosystem, build production-ready AI agents, and collaborate with AI scientists to translate experiments into reliable software.

You will thrive by crafting clean code, owning software quality end-to-end, and staying current with AI innovations to improve product capabilities and developer productivity.