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Principal Machine Learning Engineer, GAI Search Relevance - Ranking - Moveworks

ServiceNow

Principal Machine Learning Engineer, GAI Search Relevance - Ranking - Moveworks

ServiceNow

Mountain View

·

On-site

·

Full-time

·

1w ago

Benefits & Perks

Healthcare

401(k)

Equity

Flexible PTO

Family Leave

Healthcare

401k

Equity

Parental Leave

Required Skills

Search Systems

Information Retrieval

Ranking

Natural Language Understanding

Machine Learning

Distributed Systems

Text Processing

Principal Machine Learning Engineer, GAI Search Relevance

  • Ranking
  • Moveworks

What You Will Do

We are seeking a Principal Engineer to lead the technical vision and long-term architecture of our GenAI Search Platform. This platform powers Moveworks’ conversational search and question-answering systems, combining advanced information retrieval with large language models (LLMs) to deliver instant, enterprise-grade answers at scale.

As a Principal Engineer, you will operate at the intersection of search, generative AI, and platform infrastructure. You will define and drive the multi-year technical strategy for our search ecosystem — ensuring it is scalable, extensible, secure, and capable of supporting the next generation of agentic and LLM-enabled experiences across the enterprise.

You will partner closely with ranking, ML, product, infrastructure, data science, and customer teams to evolve our search platform into a foundational capability that enables rapid innovation while maintaining rigorous guarantees around quality, privacy, and reliability.

Key Responsibilities

Set Technical Vision & Architecture:

  • Define and evolve the long-term architecture of our GenAI search platform, balancing classical information retrieval techniques with LLM-driven retrieval-augmented generation (RAG) systems.

  • Architect scalable abstractions and frameworks that enable multiple teams (ranking, product, ML) to safely and independently build on top of the platform.

  • Establish durable design principles for performance, enterprise readiness, extensibility, and observability.

Drive Next-Generation Search Capabilities:

  • Lead the development of advanced conversational search systems, including multi-turn, multi-hop, and agentic workflows.

  • Define architectural patterns for integrating LLMs into search systems in a secure, cost-efficient, and production-grade manner.

  • Ensure the platform can support rapid experimentation while enforcing guarantees around security, privacy, and compliance in enterprise environments.

Platform Quality & Evaluation Strategy:

  • Establish systematic evaluation methodologies and metrics for search and generative systems, including LLM-assisted evaluation frameworks.

  • Lead the definition of quality standards for ranking, retrieval accuracy, hallucination mitigation, and user trust.

  • Champion performance optimization, scalability, and operational excellence across the platform.

Cross-Functional Technical Leadership:

  • Influence product and engineering roadmaps to align with platform strategy and long-term scalability goals.

  • Serve as a technical advisor across teams, ensuring architectural coherence and reducing fragmentation.

  • Drive high-leverage initiatives that unlock velocity for multiple product teams.

Organizational Impact

  • Mentor and elevate senior and staff engineers.

  • Shape hiring strategy and help close top technical talent.

  • Raise the bar for engineering excellence, documentation, design rigor, and code quality across the organization.

What You Bring to the Table

  • 8+ years of engineering experience, with a track record of leading large-scale technical initiatives across teams.

  • Demonstrated experience operating at Staff/Principal scope, driving architecture and influencing technical direction beyond a single team.

  • Deep expertise in search systems, information retrieval, ranking, recommendation systems, or large-scale question-answering platforms.

  • Strong background in text processing, natural language understanding, and/or applied machine learning.

  • Experience designing distributed systems that operate at enterprise scale with high reliability and performance requirements.

  • A systems thinker who balances innovation with pragmatism in production environments.

Nice to Have

  • Experience with large language models, retrieval-augmented generation (RAG), or agent-based architectures.

  • Experience productionizing LLM systems with attention to cost, latency, evaluation, and safety.

  • Strong Python experience, particularly contributing to platform-level libraries or shared infrastructure.

  • Familiarity with Golang or other backend systems languages.

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+

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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