Senior Staff Machine Learning Engineer

Reposted 10 Days Ago
Hiring Remotely in Santa Clara, CA
Remote or Hybrid
Senior level
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
We're putting AI to work for people.
The Role
As a Senior Staff Machine Learning Engineer, you will design and implement infrastructure for AI workloads, collaborate with teams to ensure system performance, and contribute to software engineering best practices while mentoring colleagues.
Summary Generated by Built In
Company Description
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
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 ServiceNow 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 Senior 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.

Qualifications
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
  • Experience with methods of training and fine tuning large language models, such as distilation, supervised fine-tunning and policy optimization
  • Experience in using AI productivity tools such as Cursor, Windsurf, etc
  • 6+ years of development experience with Python, GoLang, Java or similar languages;
  • 8+ years of experience with infrastructure and platform operations, deployments, SRE, and DevOps with a continued focus on improving Platform health;
  • 6+ 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.

Additional Information
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 ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
Equal Opportunity Employer
ServiceNow 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 [email protected] 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), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow 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.

Top Skills

Ai Productivity Tools
Ansible
Gitlab Ci
Go
Helm
Infrastructure As Code
J2Ee
Java
Kubernetes
Linux
Prometheus
Python
Software-Defined Networking
Splunk

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The Company
HQ: Santa Clara, CA
27,000 Employees
Year Founded: 2004

What We Do

As the AI platform for business transformation, we're putting AI to work across organizations — freeing people for work that matters. Making old tech work with new tech. Reaching across departments, from the front office to the back office and every office in between. Our ambition? To become the defining enterprise software company of the 21st century (or "DESCO21C," as we like to call it).

With more than 8,100+ customers, we serve approximately 85% of the Fortune 500®, and we're proud to be a Fortune 100 Best Companies to Work For® and World's Most Admired Companies™.

Explore your future career with us, visit www.servicenow.com/careers.

From Fortune. ©2024 Fortune Media IP Limited. All rights reserved. Used under license.

Why Work With Us

By joining ServiceNow, you are part of an ambitious team of change-makers who have a restless curiosity and a drive for ingenuity. We're committed to helping our people do their best work and live their best lives so we can fulfill our purpose together. At the fastest-growing enterprise software company , you can grow can grow your career faster.

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ServiceNow Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

At ServiceNow, we lead with flexibility and trust. For some, home is the primary workplace. For those who come into a ServiceNow workplace, you are empowered to make team-guided and individual-led decisions on how and when you use the workplace.

Typical time on-site: Flexible
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