Staff Machine Learning Engineer

Staff Machine Learning Engineer

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.

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 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
• 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
• 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.
• 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.