Staff Machine Learning Engineer

ServiceNow•Santa Clara, CA

2d•Hybrid

About The Position

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 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.

Requirements

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, GoLang, 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.

Nice To Haves

4+ years of experience with infrastructure and platform operations, deployments, SRE, and DevOps with a continued focus on improving Platform health

Responsibilities

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.