Senior Machine Learning Engineer

Senior Machine Learning Engineer

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

About the team:

The Agentic AI team is a platform engineering group responsible for building ServiceNow's AI Agents framework —the foundational infrastructure that enables product teams and customers to create intelligent, autonomous agents. We design and develop agentic pipelines using Python and Java, delivering capabilities such as agent reasoning, memory, orchestration, and evaluation at enterprise scale.

Beyond core platform development, engineers on this team have the opportunity to contribute to research initiatives in agent learning, agentic evaluation methodologies, and analytics. We embrace the rapidly evolving landscape of LLMs and Agentic AI while maintaining the reliability and performance standards required to operate at ServiceNow's scale.

What you get to do in this role:

• Design, implement, and optimize LLM pipelines using frameworks such as LangChain, LangGraph, and vendor APIs (OpenAI, Anthropic, etc.).
• Write clean, efficient, and scalable code in Python and Java, applying best practices in ML engineering and enterprise application development.
• Develop and refine prompt engineering strategies and agent reasoning workflows to improve accuracy and reliability.
• Build and maintain evaluation frameworks for measuring model performance, including custom metrics for agent instructions and reasoning.
• Debug, profile, and optimize inference pipelines for latency and cost efficiency at scale.
• Collaborate closely with product teams to translate business needs into technical implementations.
• Contribute to end-to-end development from prototyping to production deployment in enterprise environments.
• Stay current with the latest advancements in LLMs, Agentic AI, and orchestration frameworks, applying new techniques where beneficial.

Qualifications

To be successful in this role you have:

• Experience in leveraging and critically evaluating AI integration into work processes, decision-making, and problem-solving. This includes using AI-powered tools, automating workflows, analyzing AI-driven insights, and exploring AI's potential impact on business functions or the industry.
• 4 to 6+ years of hands-on experience designing and building AI/ML pipelines and solutions, with a strong emphasis on scalable, production-grade applications.
• Proficiency in Python (ML libraries and GenAI/LLM frameworks) and Java for enterprise application development and object-oriented design.
• Practical experience with LLM frameworks such as LangChain and LangGraph, as well as leading vendor SDKs and APIs (OpenAI, Anthropic, etc.).
• Strong expertise in prompt engineering and designing agentic reasoning workflows and pipelines.
• Solid understanding of ML evaluation techniques, with hands-on experience implementing model monitoring and metrics.
• Proven ability to debug and optimize inference pipelines for both performance and cost efficiency.
• Strong problem-solving skills with the ability to thrive in fast-paced, agile development environments.
• Nice to have: Contributions to open-source projects, technical blogs, or papers related to LLMs and GenAI.