Machine Learning Engineer

H&R Block is a tax services company focused on providing help and inspiring confidence through human expertise and digital innovation. The Machine Learning Engineer will design, develop, deploy, optimize, and maintain machine learning and generative AI models, collaborating with MLOps Engineers and cross-functional teams to deliver scalable AI solutions.

Responsibilities:

• Model Development: Design, build, and deploy machine learning models—including generative AI models—to address complex business problems
• Data Collaboration: Work with teammates to preprocess, clean, and analyze structured and unstructured data for use in ML pipelines
• Performance Optimization: Tune and optimize models for accuracy, efficiency, and scalability in production environments
• Integration Support: Collaborate with MLOps Engineers to ensure smooth deployment, monitoring, and maintenance of ML models
• Continuous Learning: Stay informed on the latest advancements in machine learning, deep learning, and generative AI technologies, and apply them where appropriate
• Team Collaboration: Contribute to a collaborative engineering culture by sharing knowledge, participating in code reviews, and supporting team initiatives

Requirements:

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field (or equivalent experience)
• 1-2 years experience
• Hands-on experience with ML frameworks such as scikit-learn, TensorFlow, PyTorch, and spaCy
• Proficiency in Python and familiarity with ML development workflows
• Strong analytical and problem-solving skills with attention to detail
• Effective communication and collaboration skills in a team-oriented environment
• Hands-on experience with building and deploying Machine Learning models for real time inference
• Master's or PhD in Computer Science, Statistics, Mathematics, or a related field (or equivalent experience)
• Experience with generative AI is a plus