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Machine Learning Engineering Manager, GAI Search Relevance - Moveworks

ServiceNow

Machine Learning Engineering Manager, GAI Search Relevance - Moveworks

ServiceNow

Mountain View

·

On-site

·

Full-time

·

1w ago

Benefits & Perks

Remote Work

Flexible Hours

Remote Work

Flexible Hours

Required Skills

Machine Learning

Python

Go

C++

Team leadership

Project management

Technical strategy

Machine Learning Engineering Manager, GAI Search Relevance

As the leader of a team of talented search relevance engineers, your objective will be to measure and improve the ranking and relevance of our AI-powered enterprise search applications. Since these applications also leverage large language models (LLMs), you will also be responsible for measuring and improving RAG-based objectives such as summarization, groundedness of responses, and citation correctness and completeness. You will guide the team to drive end-to-end development of machine-learning models, including data synthesis, feature engineering, experiment design, evaluation and more. Your team will play a pivotal role in improving our search relevance in a systematic and methodical manner as we scale to new customers, new types of data and use-cases, and will ultimately be accountable for the ranking quality of all our enterprise search products.

Your team's ownership of search quality is crucial to the company's search product lines, with success measured by its enablement capabilities. You will enable your team members by facilitating rapid iteration on model enhancements, allowing them to improve ML metrics with a clear understanding of performance tradeoffs and generalizability.

You will be responsible for guiding the team's technical direction, managing project timelines, and ensuring the robustness, efficiency, and innovation of our machine learning based search systems. Your team will collaborate closely with search infrastructure and platform engineers, and partner with product, design, and customer success teams to jointly achieve business objectives.

What You Will Do:

  • Team Leadership:Recruit, hire, and mentor a high-performing team of machine learning engineers.
  • Maintain a “ranking and relevance” mindset in your team, developing a thought leadership on our long-term relevance roadmap.
  • Foster a collaborative and inclusive team culture, promoting knowledge sharing and continuous learning.
  • Set clear goals, provide regular feedback, and promote professional growth and development of team members.
  • Project Management:Develop and manage project plans, timelines, and budgets for machine learning initiatives.
  • Ensure the successful execution of projects, from ideation and prototyping to production deployment.
  • Collaborate with cross-functional teams to define project requirements and priorities.
  • Technical Leadership:Drive the technical vision and strategy.
  • Guide the integration and application of large language models (LLMs) and retrieval-augmented generation (RAG) techniques to enable modern, intelligent search experiences.
  • Oversee the research, development, and deployment of machine learning models and algorithms.
  • Stay current with the latest advancements in the field and ensure that our projects leverage cutting-edge technologies.
  • Quality and Performance:Implement best practices for model development, data pipelines, and model evaluation.
  • Monitor and optimize the performance, scalability, and reliability of machine learning systems.
  • Ensure that our AI solutions meet high standards of accuracy and efficiency.
  • Stakeholder Communication:Collaborate with leadership, product managers, customer success staff, and other teams to align machine learning initiatives with business goals.
  • Provide regular updates and reports on project status, challenges, and successes to stakeholders.
  • Communicate, collaborate, and build relationships with partner teams and peer teams to facilitate cross-functional projects

What you bring to the table:

  • Master's degree in Computer Science specializing in Machine Learning or a related field. A Ph.D. is a plus.
  • 8+ years of experience in applied machine learning preferably in the ranking/relevance domain, including 3+ years in technical leadership or management roles.
  • Proven technical expertise that has been recognized at Staff Engineer (comparable to Google/Meta L6) or above level.
  • Proven experience managing high-performing teams, including mentoring and supporting Staff-level (I6) or higher engineers, with a strong track record of delivering technically ambitious, production-grade projects.
  • Proficiency in programming languages such as Python, Golang, C++.
  • Excellent problem-solving and analytical skills.
  • Strong communication skills.
  • Knowledge of software engineering best practices and experience with deploying machine learning models in production environments.

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to Service Now employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, Service Now may confirm the distance between your primary residence and the closest Service Now office using a third-party service.

Equal Opportunity Employer

Service Now is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), Service Now may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon Service Now obtaining any export license or other approval that may be required by relevant export control authorities.

From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

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 — Service Now 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.

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About ServiceNow

ServiceNow

ServiceNow, Inc. is an American software company that supplies a cloud computing platform for the creation and management of automated business workflows. The company was founded in Santa Clara, California, United States, in 2003 by Fred Luddy.

10,001+

Employees

Santa Clara

Headquarters

Reviews

3.9

25 reviews

Work Life Balance

3.2

Compensation

3.8

Culture

2.8

Career

3.5

Management

2.9

45%

Recommend to a Friend

Pros

Good compensation and benefits package

Learning opportunities and skill development

Work-life balance emphasis and flexible remote options

Cons

Toxic management and politics

Heavy bureaucracy and slow decision making

Layoffs and restructuring uncertainties

Salary Ranges

31 data points

Junior/L3

Junior/L3 · Data Informatics Analyst

1 reports

$77,167

total / year

Base

$67,059

Stock

-

Bonus

-

$77,167

$77,167

Interview Experience

11 interviews

Difficulty

2.8

/ 5

Duration

14-28 weeks

Offer Rate

45%

Experience

Positive 18%

Neutral 82%

Negative 0%

Interview Process

1

Application Review

2

Phone Screen/Online Assessment

3

Technical Interview

4

Behavioral Interview

5

Final Round/Panel Interview

6

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience