Senior Staff Machine Learning Engineer

ServiceNow•Santa Clara, CA

27d•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.â We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences.â 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:

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
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.

Responsibilities

Contribute to the design, development andâ 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, scalableâ and reusable code by enforcing bestâ practices around softwareâ engineering architecture andâ processes (Code Reviews, Unitâ testing, etc.);
Work with the productâ owners to understand detailedâ requirements and own your codeâ from design, implementation, testâ automation and delivery of high-quality product to ourâ users;
Experience with operating LLMs on NVIDIA GPUs.
Be a mentor for colleagues andâ help promote knowledge-sharing.