Job Description:
Day to day, you'll...
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- Define and drive the technical strategy
- Develop and implement the overall MLOps vision and roadmap, ensuring alignment with business goals
- Design and build scalable ml pipelines
- Architect and develop end-to-end pipelines for continuous model integration, deployment, and monitoring
- Implement infrastructure automation
- Lead the use of infrastructure-as-code, CI/CD pipelines, containerization, and orchestration tools (e.g., Docker, Kubernetes) to streamline deployments
- Provide technical leadership and mentorship
- Guide and mentor junior engineers, foster best practices, and encourage continuous skill development across the team
- Collaborate across teams
- Work closely with data scientists, software engineers, and product managers to understand requirements and translate them into robust production systems
- Ensure monitoring and model governance
- Establish monitoring, logging, and alerting systems to proactively manage model performance and data drift
- Drive innovation and stay current
- Evaluate emerging MLOps tools and techniques, and recommend enhancements to maintain our competitive edge
About H&R Block...
H&R Block’s purpose is simple: To provide help and inspire confidence in our clients and communities everywhere. We’ve been true to that purpose since brothers Henry and Richard Bloch founded our company in 1955. Since then, we’ve grown to have approximately 12,000 offices throughout the United States and around the world.
We are a people company first and a tax company second. People who join H&R Block say it feels like being part of something bigger. A place with an amazing and storied history, but with a strong and urgent focus on the future. Maybe it’s how determined, forward thinking and innovative we are, or how accessible our leadership is. We believe it’s all those things, and much more.
H&R Block is committed to diversity and inclusion and is proud to be an equal opportunity employer. We consider qualified applicants regardless of race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. All qualified applicants are welcomed and encouraged to apply.
It would be even better if you also had...- MS or PhD in a technical field is highly desirable
- Relevant cloud certifications (e.g., AWS Certified Machine Learning – Specialty) and MLOps credentials
- Experience with big data technologies (e.g., Apache Spark, Hadoop) and real-time inference architectures
- Bachelor's or master's degree in computer science, data science, engineering, or a related field
- 8+ years of industry experience, with at least 3 years in a leadership or technical lead role in MLOps or related fields
- Expert-level knowledge of cloud platforms (AWS, Azure, or GCP) and hands-on experience with infrastructure-as-code tools (e.g., Terraform)
- Advanced skills in Python and familiarity with popular machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- Proven experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipeline tools (e.g., Jenkins, GitLab CI)
- Strong background in setting up monitoring, logging, and automation frameworks to ensure model reliability and scalability
- Excellent communication, problem-solving, and collaboration skills; demonstrated ability to lead technical teams and manage complex projects