Senior AI/ML Data Science Engineer

Jack Henry & Associates is a technology company focused on redefining financial services for community banks and credit unions. The Senior AI/ML Data Science Engineer will design and build platforms for AI/ML, ensuring high availability and reliability while collaborating with cross-functional teams to implement predictive models and enhance client product experiences.

Responsibilities:

• Architect & Evolve: Design and build the platforms and applications that serve as the backbone for AI/ML at Jack Henry
• Full-Stack ML Engineering: Work across backend services and application layers to optimize AI/ML systems for high availability and low-latency inference
• Cross-Functional: Implement predictive models and multimodal integrations that solve complex financial services challenges
• Foundational Development: Build scalable RESTful APIs and platform components that allow teams to leverage AI/ML foundations seamlessly
• Security & Safety: Solve unique challenges in AI/ML safety, data security, and ethical model deployment
• Operational Excellence: Deliver production-ready code, ensuring every system meets rigorous standards for performance, scalability, and maintainability
• Develops and evaluates predictive models and algorithms to optimize data value extraction
• Collaborates with engineers to translate prototypes into production-ready products, services, and features, providing guidance for large-scale implementation
• Enhances client product experience through data analysis, ad-hoc analytics, and performance metrics
• Explores and analyzes data from multiple disparate sources, uncovering hidden insights to provide competitive advantages or address pressing business problems
• Collaborates with cross-functional teams to assemble and synthesize training datasets from diverse data sources within the data lake
• Prototypes, refines, develops, deploys, and scales machine learning models for AI products
• Communicates informed conclusions and recommendations effectively to business and IT teams, influencing organizational approaches to business challenges
• Selects high-value problems aligned with organizational strategic priorities
• May mentor less experienced peers and/or act as a team lead
• May perform other job duties as assigned

Requirements:

• Minimum of 6 years of experience in data engineering, ML engineering, or MLOps roles
• Demonstrated ownership of end-to-end ML pipelines from feature engineering to live model serving
• Experience in regulated or financial services industries a strong plus (payments, fraud, banking, insurance)
• Proficiency in containerization (Docker) and orchestration concepts relevant to ML workloads
• Infrastructure-as-code experience with Terraform for GCP resource management
• Version control best practices with Git; comfortable in trunk-based development and PR-review workflows
• Working knowledge of REST API design for model serving, and gRPC/Protocol Buffers a plus
• Strong collaborator and team player. Fosters a positive and productive team environment