Machine Learning Ops Engineer

H&R Block is a leading company in the tax industry that blends human expertise with digital innovation. They are seeking a Machine Learning Ops Engineer responsible for building and maintaining the infrastructure for machine learning models, ensuring their scalability and reliability in production environments.

Responsibilities:

• Work closely with data scientists and other MLOps engineers to streamline workflows, automate processes, and ensure the scalability and reliability of ML systems in production environments
• Ensure that the team is able to offer machine learning model predictions at scale
• Devlier reliable, scalable ML systems that enable teams to move models from experimentation to production quickly and safely, while maintaining high standards for performance, security, and operational excellence

Requirements:

• Bachelor's degree in a related field or the equivalent through a combination of education and related work experience
• Ability to collaborate and solve problems effectively with excellent cross-team collaboration and communication skills
• Experience with Git
• Familiarity with cloud platforms such as AWS, Azure, or GCP, including deploying and operating services in cloud environments
• 3 years minimum related work experience
• Proficiency in Python and experience applying software engineering best practices (version control, testing, and code reviews)
• Strong problem solving skills, attention to detail, and ability to troubleshoot production issues
• Working knowledge of model governance concepts, including model versioning, experiment tracking, reproducibility, and rollback strategies
• Experience with Databricks, Azure Pipelines, and major cloud platforms (AWS, Azure, and GCP)
• Experience with Docker, Kubernetes, SQL, and enterprise scale data management practices
• Working knowledge of Generative AI technologies and their operational considerations