ServiceNow

Senior Staff Machine Learning Engineer, Agentic Systems - Moveworks

Mountain View, CALIFORNIA, United States · On-site · Full-time

Apply on the employer’s site ↗See how well you match this job

You apply directly with the employer. ROLIVA does not submit applications from this page and is not the employer.

About the role

Description from the employer’s posting. Check the employer’s page for the current version.

EmployerServiceNow
LocationMountain View, CALIFORNIA, 94043, United States
Work styleOn-site
Employment typeFull-time
Employer posted1 month ago

The Role

We are looking for a Machine Learning Engineer to help build cutting edge ML infrastructure for building and serving LLM’s at Moveworks. This role will be critical in building, optimizing and scaling end-to-end machine learning systems. The ML infra team covers a variety of responsibilities including distributed training and inference pipeline for large language models(LLM), model evaluation and monitoring framework, LLM latency optimization, etc. These frameworks serve as a strong foundation for our hundreds of ML and NLP models in production serving hundreds of millions of enterprise employees. We are solving many challenges on scalability of services as well as optimization of core algorithms.

In this role you will work closely with our machine learning team, data infrastructure team and every core skill. Above all, your work will impact the way our customers experience AI. Put another way, this role is absolutely critical to the long term scalability of our core AI product and ultimately the company. You will be responsible for building and productionizing ML infrastructure that runs state of the art models. If you are looking for a high-impact, fast-moving role to take your work to the next level, we should have a conversation.

Show full description

Design, build and optimize scalable machine learning infrastructure to support training, evaluation, and deployment of large language models.
Build abstractions to automate various steps in different ML workflows
Collaborate with cross functional teams of engineers, data analytics, machine learning experts, and product to build new features
Leverage your experience to drive best practices in ML and data engineering

What you get to do in this role:

Design, build and optimize scalable machine learning infrastructure to support training, evaluation, and deployment of large language models.
Build abstractions to automate various steps in different ML workflows
Collaborate with cross functional teams of engineers, data analytics, machine learning experts, and product to build new features
Leverage your experience to drive best practices in ML and data engineering

To be successful in this role you have:

US Citizenship or permanent resident status
12+ years of industry experience in Machine Learning, Infrastructure or related fields
Experience with deep learning framework such as Pytorch or Huggingface or LLM serving frameworks such as vLLM or TensorRT-LLM.
Experience with building and scaling end-to-end machine learning systems
Experience building scalable micro services and ETL pipelines
Expertise in Python and experience with performant language such as C++ or GoLang
Bachelor's in Computer Science, Computer Engineering, Mathematics, or equivalent field.
A love of research publications in the machine learning and software engineering communities
Effective communicator with experience collaborating cross-functionally with other teams

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 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), 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.

See how well you match this job Apply on the employer’s site ↗

Check your resume against this job Free, no sign-up. Nothing you paste is stored.

Staying safe while you apply

Never pay to apply, interview or accept an offer. ROLIVA never asks you for payment to apply to a job.
Apply only through the official “Apply on the employer’s site” button, on the employer’s own site, and check that a recruiter’s email uses that employer’s own domain rather than a free email address.
Be cautious of an offer made with no real interview, or pressure to decide quickly or share financial details early.

Does something look wrong with this listing? Use “Report broken link” in the role details, or read ROLIVA’s full job-safety guidance ↗.

Preparing for this role with ROLIVA

Check the fit.
Compare the requirements with the experience you have confirmed, including gaps.
Prepare honestly.
Build interview stories and application drafts from your own evidence.
Keep track.
Save the role and record your own application status and follow-ups.

Create a free workspace or log in.