Staff ML Application Developer

Company Description

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.

Job Description

What you get to do in this role:

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 AI/ML products, and enable the operationalization and reliability of all AI. 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 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 AI 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 entire MLOps Platform team to build a comprehensive MLOps 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.
• Write code, refactoring, optimizing, containerization, deployment, versioning, and monitoring of its quality, including data & concept drift.
• Create way to automate the testing, validation, and deployment of data science models.
• Mentor Junior MLOps Engineers and help teach them to be better coders, debuggers, and engineers.
• Provide best practices and execute POC for automated and efficient MLOps at scale.

Qualifications

Requirements:

• 8+ years of related experience with a Bachelor's degree, Masters degree or PhD or equivalent work experience.
• 8+ 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, Terraform, etc.).
• Strong communication and collaboration skills.
• Ability to mentor engineers and help them become better.
• Ability to help work with a team to create User Stories and Tasks out of higher level requirements.

Preferred:

• Masters and/or PHD degree preferred.
• Building a AI and/or ML Platform using Azure Databricks
• Experience with Azure
• Ability to create model inference systems with advanced deployment methods that allow progress rollouts and automated validation.
• Knowledge of inference systems.
• Knowledge of deploying applications and systems in Kubernetes using Helm and Helmfile.
• Experience with containerization technologies like Docker and Kubernetes.
• Knowledge of infrastructure orchestration using Terragrunt and Terraform.
• Exposure to building and using feature stores.
• Exposure to observability applied to AI and ML.
• Have experience building apps on ServiceNow

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!

Additional Information

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 globaltalentss@servicenow.com 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. 

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