Senior Machine Learning Engineer Ii (AI)

TL;DR

Senior Machine Learning Engineer (AI): Building the intelligence behind agentic AI systems that reason over massive log data with an accent on machine learning, prompt engineering, and evaluation to create autonomous AI agents. Focus on cutting-edge LLM infrastructure and defining best practices in context engineering and AI observability.

Location: Must be authorized to work in the United States at the time of hire and for the duration of employment. At this time, we are not able to offer new non-immigrant visa sponsorship for this position.

Salary: $148,000 - $173,200

Company

hirify.global is a cloud-native SaaS data analytics platform that solves complex observability and security problems.

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 at scale.
• 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 AI-powered insights.
• Operate autonomously in a fast-paced, ambiguous environment, defining scope and driving outcomes.
• Ensure reliability, performance, and observability of deployed agents through testing and continuous improvement.

Requirements

• B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field.
• 4-6 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; familiarity with JVM languages is a plus.
• Working knowledge of LLM core concepts, prompt design, and agentic design patterns.
• Prior experience building and deploying AI agents or LLM applications in production.

Nice to have

• Authored research/white papers and published in conferences.
• Mentored junior engineers in guiding ML applications

Culture & Benefits

• Solve complex observability and security problems with a cloud-native SaaS data analytics platform.
• Work on a microservices architecture hosted on AWS, ingesting petabytes of data daily.
• Gain trusted insights to protect against security threats and ensure reliability for customers worldwide.