ML Engineer II (AI)

Location: Remote USA

Salary: $110,000–$130,000 base salary per year, plus a discretionary bonus or commission and benefits.

Company

hirify.global provides experience measurement, data analytics, and insights, with roots in healthcare and technology that help organizations improve human experiences.

What you will do

• Build, test, and deploy production-ready AI agents and agentic workflows for enterprise applications and business processes.
• Develop and maintain AI-enabled features within a Java and Spring platform and distributed microservices ecosystem.
• Implement evaluation, monitoring, guardrail, and safety frameworks for LLM-powered applications.
• Collaborate with AI Scientists and ML Engineers to productionize models and convert experimentation into reliable software.
• Participate in design reviews, technical discussions, requirement planning, prototyping, and agile delivery.
• Evaluate emerging AI technologies and recommend practical adoption strategies.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience.
• 2–5 years of hands-on Machine Learning Engineer experience building and optimizing production ML models with PyTorch or TensorFlow.
• Strong foundations in data structures, algorithms, complexity analysis, performance optimization, and object-oriented development.
• Proficiency in Python, Java, or C#, with experience developing and supporting machine learning services in enterprise software ecosystems.
• Experience building production-grade LLM applications with technologies such as LangChain, LangGraph, Spring AI, or Model Context Protocol, plus RAG, tool calling, and prompt engineering.
• Experience with observability, CI/CD, automated testing, and production operations for AI applications.

Nice to have

• Experience with Databricks, vector search, embedding models, conversational AI, and AI-agent evaluation strategies.
• Experience building large-scale Java microservices with Spring Boot.
• Experience with AWS, Azure, or GCP, Kubernetes, and containerized deployments.
• Familiarity with model serving, inference optimization, caching, and cost optimization for enterprise AI systems.

Culture & Benefits

• Full-time employment with a competitive benefits package.
• Collaborative work across AI, engineering, technology operations, and product teams.
• Learning and continuous improvement are emphasized through technical discussions and peer collaboration.
• Eligible employees may receive a discretionary bonus or commission tied to achieved results.
• Reasonable accommodations are available during the hiring process for qualified individuals with disabilities or disabled veterans.