Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Building intelligence for next-generation agentic AI systems that reason over massive, heterogeneous log data, with an accent on machine learning, prompt engineering, and rigorous evaluation. Focus on creating autonomous AI agents to help organizations understand and act on their data in real time, shaping how AI agents understand complex machine data, and contributing to defining best practices in context engineering and AI observability.

Location: Must be authorized to work in the United States

Salary: $148,000–$173,200

Company

hirify.global, Inc. provides an Intelligent Operations Platform that unifies critical security and operational data, enabling digital teams to move from reaction to readiness and gain powerful insights into their digital environments.

What you will do

• Design, implement, and optimize agentic AI components, including context engineering, memory management, and prompts.
• Develop and maintain golden datasets by defining sourcing strategies and ensuring quality and representativeness.
• Prototype and evaluate novel prompting strategies and reasoning chains for model reliability and interpretability.
• Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights.
• Operate autonomously in a fast-paced, ambiguous environment, defining scope, setting milestones, and driving outcomes.
• Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement.

Requirements

• B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field.
• 2-5 years of hands-on industry experience with demonstrable ownership and delivery.
• Strong understanding of machine learning fundamentals, data pipelines, and model evaluation.
• Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn).
• Working knowledge of LLM core concepts, prompt design, and agentic design patterns.
• Strong communication skills and a passion for shaping emerging AI paradigms.
• Must be authorized to work in the United States at the time of hire and for the duration of employment.

Nice to have

• Prior experience building and deploying AI agents or LLM applications in production.
• Familiarity with modern agentic AI frameworks (e.g., LangGraph, LangChain, CrewAI).
• Experience with ML infrastructure and tooling (PyTorch, MLflow, Airflow, Docker, AWS).
• Exposure to LLM Ops - infrastructure optimization, observability, latency, and cost monitoring.

Culture & Benefits

• Eligible to participate in bonus or commission plans.
• Access to benefits offerings and equity awards.