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Staff Machine Learning Engineer

ServiceNow

Staff Machine Learning Engineer

ServiceNow

Santa Clara

·

On-site

·

Full-time

·

1w ago

Compensation

$173,100 - $303,000

Benefits & Perks

Healthcare

401(k)

Equity

Flexible Hours

Parental Leave

Healthcare

401k

Equity

Flexible Hours

Parental Leave

Required Skills

Python

Go

Java

Kubernetes

DevOps

Prompt Engineering

LLM

Linux

SIP Protocol

What you get to do in this role:

Please note that this role requires you to be in our Santa Clara office for two days per week.

PLATO (Platform Engineering and AI Technology Organization) at Service Now is a customer-focused innovative group building intelligent software using a variety of technology stacks to enable end-to-end, industry-leading work experiences for our customers. We are a group of people deeply invested in the success of our customers that happen to have expertise and knowledge in advanced technologies and software engineering best practices. We are data driven, structured, committed and we enjoy what we are doing. We prioritize robustness, performance and user experience over the technology stack and tools.

We are a group of technology professionals and platform engineers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future.

As a Staff Machine Learning Engineer you will:

  • Contribute to the design, development and implementation of infrastructure, platform, deployment and observability features that power AI workloads.
  • Collaborate with researchers, AI engineers, and infrastructure teams to ensure our GPU clusters perform efficiently, scale well, and remain reliable.
  • Contribute to the continuous improvement of the SRE practice by turning operational use cases into requirements for software tooling.
  • Contribute to the execution of deployment and support activities for AI/ML developers;
  • Build high-quality, clean, scalable and reusable code by enforcing best practices around software engineering architecture and processes (Code Reviews, Unit testing, etc.);
  • Work with the product owners to understand detailed requirements and own your code from design, implementation, test automation and delivery of high-quality product to our users;
  • Experience with operating LLMs on NVIDIA GPUs.
  • Be a mentor for colleagues and help promote knowledge-sharing.

To be successful in this role you have:

  • Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.
  • Proficient in prompt engineering and developing LLM based features
  • Working experience building VoIP systems using SIP protocol and SBC/PBX/PSTN infrastructures
  • Experience in using AI productivity tools such as Cursor, Windsurf, etc
  • Exposure with operating LLMs on NVIDIA GPUs.
  • 4+ years of development experience with Python, Go Lang, Java or similar languages.
  • 4+ years of experience operating highly available distributed workloads on Kubernetes following a DevOps approach.
  • Experience with DevOps tooling (e.g. Helm / Ansible / Kubernetes / Prometheus /Splunk/ GitLab CI);
  • Strong working experience operating distributed systems built on Linux and J2EE;
  • Experience with software-defined networking, infrastructure as code and configuration management;
  • Experience building software for compliance and security in regulated environments
  • Ability to drive outcome in projects with material technical risk.
  • Asset: 4+ years of experience with infrastructure and platform operations, deployments, SRE, and DevOps with a continued focus on improving Platform health;

For positions in this location, we offer a base pay of $173,100 - $303,000, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

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