ML Engineering Manager, AI Search Relevance

ServiceNow; Mountain View (CA); On-site; USD 139,700 - 216,500; Full time

Benefits offered by this job

Health plans

401(k) Plan with company match

ESPP

Flexible time away plan

Family leave programs

Job summary

ServiceNow is seeking a Machine Learning Engineering Manager for GAI Search Relevance. Lead a team of ML engineers to improve ranking and relevance of AI-powered enterprise search applications, leveraging LLMs and retrieval-augmented generation.

Drive end-to-end ML model development, data synthesis, feature engineering, experiments, and production deployment. You will guide technical direction, manage timelines, collaborate with product, design, and customer success teams, and ensure scalable,

Qualifications

• 8+ years in applied ML, preferably in ranking/relevance domains.
• 3+ years in technical leadership or management roles.
• Proven experience mentoring and delivering production-grade ML projects.
• Proficiency in Python, Golang and C++.

Responsibilities

• Recruit, hire, and mentor a high-performing ML engineering team.
• Maintain a ranking and relevance mindset and develop the long-term relevance roadmap.
• Foster collaborative culture and continuous learning across teams.
• Set goals, provide feedback, and support professional growth of team members.
• Develop and manage project plans, timelines, budgets for ML initiatives.
• Drive technical vision, evaluating LLMs and RAG techniques for modern search.
• Oversee ML model research, development, deployment, and scaling.
• Ensure quality, performance, and reliability of ML systems.
• Communicate status, challenges, and outcomes to stakeholders.

Skills

Leadership

Staff Engineer level

Python

Golang

C++

Production ML

Education

Master's degree in Computer Science specializing in ML

PhD in related field (a plus)

Job description

ServiceNow is seeking a Machine Learning Engineering Manager for GAI Search Relevance. Lead a team of ML engineers to improve ranking and relevance of AI-powered enterprise search applications, leveraging LLMs and retrieval-augmented generation.

Drive end-to-end ML model development, data synthesis, feature engineering, experiments, and production deployment. You will guide technical direction, manage timelines, collaborate with product, design, and customer success teams, and ensure scalable,