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Senior MLOps Engineer

Company Description

At ServiceNow, our technology makes the world work for everyone, and our people make it possible. We move fast because the world can’t wait, and we innovate in ways no one else can for our customers and communities. By joining ServiceNow, you are part of an ambitious team of change makers who have a restless curiosity and a drive for ingenuity. We know that your best work happens when you live your best life and share your unique talents, so we do everything we can to make that possible. We dream big together, supporting each other to make our individual and collective dreams come true. The future is ours, and it starts with you. 

With more than 7,700+ customers, we serve approximately 85% of the Fortune 500®, and we're proud to be one of FORTUNE 100 Best Companies to Work For® and World's Most Admired Companies™.

Learn more on Life at Now blog and hear from our employees about their experiences working at ServiceNow.

Unsure if you meet all the qualifications of a job description but are deeply excited about the role? We still encourage you to apply! At ServiceNow, we are committed to creating an inclusive environment where all voices are heard, valued, and respected. We welcome all candidates, including individuals from non-traditional, varied backgrounds, that might not come from a typical path connected to this role. We believe skills and experience are transferrable, and the desire to dream big makes for great candidates.

Job Description

What you get to do in this role:

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

Responsibilities:

  • Help implement scalable and secure architectures, frameworks and pipelines for building, deploying and diagnosing production ML applications
  • Writing code, testing, debugging, deploying and providing operational support for the MLOps Platform
  • Collaborate with internal team members to build a comprehensive MLOps Platform
  • Design and implement cloud-based solutions (e.g., MS Azure)
  • Develop documentation, examples, videos to drive platform adoption.
  • Create way to automate the testing, validation, and deployment of machine learning models

Qualifications

Requirements:

  • 5+ years of related experience with a Bachelor's degree, Masters degree or PhD or equivalent work experience.
  • 5+ years of experience working with an object-oriented programming language (Scala, Python, Java, C/C++ etc.)
  • Proficiency in programming (Python, R, SQL)
  • Ability to 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, Airflow, etc.)
  • Experience with containerization technologies like Docker and Kubernetes
  • Strong communication and collaboration skills
  • Ability to work in an Agile manner with a team to write User Stories and Tasks from higher level requirements.

Preferred:

  • Masters and/or PHD degree preferred.
  • Experience with MLOps frameworks like MLflow, Kubeflow, etc.
  • Ability to create model inference systems with advanced deployment methods that integrate with other MLOps components like MLFlow.
  • Knowledge of inference systems like Seldon, 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 Feathr, Feast, Tecton, etc.)
  • Exposure to observability tools (such as Evidently AI, WhyLogs, etc.)

FD21

Additional Information

ServiceNow is an Equal Employment 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.

At ServiceNow, we lead with flexibility and trust in our distributed world of work. Click here to learn about our work personas: flexible, remote and required-in-office.

If you require a reasonable accommodation to complete any part of the application process, or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact us at talent.acquisition@servicenow.com for assistance.

For positions requiring access to technical data subject to export control regulations, including Export Administration Regulations (EAR), ServiceNow may have to obtain export licensing approval from the U.S. Government for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by the U.S. Government.

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