Azure ML Ops Engineer

Key Skills

Wordpress, Java Programming, Python Programming, SQL, Azure, Scala Programming, Pandas, PySpark, Hubspot, Databricks

Job Description

As an Azure ML Ops Engineer, you will work with Data Scientists and Data Architects to translate prototypes into scalable solutions. You will build, ship, run and monitor Coca-Cola’s global ML & AI solutions bridging the gap between Data Scientists and Operations. You will ensure that models conform to the ML strategy and guidance established by the Coca-Cola Data Science team. You should be proficient at building, training, deploying, and monitoring ML models on the Azure platform including Azure Machine Learning service and Synapse.

Function Related Activities/Key Responsibilities:

• Partner with Data Science organization to scale & operationalize ML & AI use-cases for both batch and real-time.
• Execute ML & AI engineering strategy, roadmap, architecture, and patterns as defined by Data Science and Engineering team.
• Comply with ML standards, guidelines, and best practices for business and technical teams laid out by Data Science organization and participate in discussions to improve standards/guidelines/best practices.
• Deploy and monitor models to in real-time (Azure Kubernetes service, Azure Container Instance service) and batch (Azure Databricks).
• Leverage CI and CD principles to automate and improve repeatability of deployments.
• Build reusable libraries to streamline and speed up work of Data Scientists.
• Modularize code to separate feature engineering and populate feature factory.
• Maintain accurate and complete technical architectural documents.
• Participate and implement ML platform governance including Azure cost analysis and Azure Policy inside managed Azure subscriptions.
• Ensure conceptual and architectural integrity of the platform and solution.
• 100% hands-on development.

Education Requirements:

• Bachelor’s Degree or higher in Computer Science, Data Science, or related technical discipline.

Related Work Experience:

• 1+ years of experience in ML Lifecycle using Azure ML (or equivalent) building datasets, ML pipelines, experiments, logging, and monitoring.
• 2+ years of experience in an execution role engaging with Data Scientists to deliver large scale analytics solutions and projects.
• 2+ years of experience in data engineering using Spark (Scala, PySpark, Pandas etc.)
• Knowledge of machine learning model training, building, algorithm selection and interpretability.
• Experience in building and managing streaming and batch inferencing.
• Experience with Azure Data Platform including Azure Synapse, Azure SQL, Cosmos DB, Event Hubs, and Service Bus.
• GitHub experience – ability to utilize CI/CD paradigm.
• Agile/Scrum operating experience using Azure DevOps.
• Personal qualities such as creativity, tenacity, curiosity, and passion for deep technical excellence.
• Experience with other public cloud ML solutions like AWS SageMaker, H2O and Vertex AI.

Our Purpose and Growth Culture:

We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what’s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors – curious, empowered, inclusive and agile – and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.