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.

We’re not yesterday’s IT department, we're Digital Technology. The world around us keeps changing and so do we. We’re redefining what it means to be IT with a mindset centered on transformation, experience, AI-driven automation, innovation, and growth. We’re all about delivering delightful, secure customer and employee experiences that accelerate ServiceNow’s journey to become the defining enterprise software company of the 21st century. And we love co-creating, using, and highlighting our own products to do it. 

Ultimately, we strive to make the world work better for our employees and customers—when you work in ServiceNow Digital Technology, you work for them. 

The AI Platform Team works within the Enterprise Data and Analytics Organization at ServiceNow driving the ability to democratize AI and machine learning to unleash data driven decisions across the enterprise, helping teams build high-value data and AI/ML products, an enable the operationalization and reliability of all models. We are searching for a driven and highly skilled MLOps Engineer to join our AI Platform team at ServiceNow. The role will build the AI Platform, build self-service tooling, and ensure our platform is effective at helping our users get their solutions to production. You have ideas on how to create a great user experience for those building , deploying, and operationalizing production quality AI and Machine Learning models. We have a team of people just as excited. Join us.

Responsibilities:

• Define scalable and secure architectures, frameworks and pipelines for building, deploying and diagnosing production ML applications
• Enable users & teams on the ML platform; troubleshoot and debug user issues; maintain user-friendly documentation and training.
• Collaborate with internal stakeholders to build a comprehensive AI Platform
• Design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., MS Azure)
• Develop standards and examples to accelerate the productivity of data science teams.
• Run code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality, including data & concept drift
• Create way to automate the testing, validation, and deployment of data science model
• Mentor Junior MLOps Engineers and be responsible for the technical delivery of a team of engineers.
• Perform one-on-ones regularly with a group of designated engineers.
• Provide best practices and execute POC for automated and efficient AI at scale

To be successful in this role you have:

• 12+ years of related experience with a Bachelor's degree; or 10 years and a Master's degree; or a PhD with 8 years' experience; or equivalent work experience
• 12+ years of experience working with an object-oriented programming language (Scala, Python, Java, C/C++ etc.)
• Experience with MLOps frameworks like MLflow, Kubeflow, etc.
• Proficiency in programming (Python, R, SQL)
• Ability to design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., MS Azure)
• Strong understanding of DevOps principles and practices, CI/CD, etc. and tools (Git, GitHub, jFrog Artifactory, Cloudbees/Jenkins, Azure DevOps, Airflow, etc.)
• Experience with containerization technologies like Docker and Kubernetes
• Strong communication and collaboration skills
• Ability to mentor a team and ensure the technical delivery of a team.
• Ability to help work with a team to create User Stories and Tasks out of higher level requirements

Desired:

• Ability to create model inference systems with advanced deployment methods that integrate with other MLOps components like MLFlow.
• Experience with Azure Databricks
• Knowledge of inference systems like KServe, Kubeflow, etc.
• Knowledge of deploying applications and systems in Kubernetes using Helm and Helmfile.
• Knowledge of infrastructure orchestration using Terragrunt and Terraform
• Exposure to enterprise feature stores (such as FeatureForm, Feast, Tecton, etc.)
• Exposure to observability tools (such as Fiddler, Evidently AI, WhyLogs, etc.)

Not sure if you meet every qualification? We still encourage you to apply! We value inclusivity, welcoming candidates from diverse backgrounds, including non-traditional paths. Unique experiences enrich our team, and the willingness to dream big makes you an exceptional candidate!

For positions in this location, we offer a base pay of $192,700 - $337,300, 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.

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. Learn more here.

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