Officer, Machine Learning & Artificial Intelligence Operations

The Machine Learning / AI Operations Engineer is responsible for ensuring the seamless deployment, monitoring, automation, and lifecycle management of AI/ML systems across the enterprise. The role ensures robust MLOps and AIOps capabilities, supports Data Scientists in operationalizing models, manages production workloads—including LLMs, RAG pipelines, and predictive models—and ensures compliance with governance and regulatory requirements.

Responsibilities

Support execution of the bank’s Data Science & AI strategy through reliable ML/AI operationalization; Design, build, and maintain end-to-end MLOps/AIOps pipelines for scalable deployment and monitoring; Work with IT, Data Engineering, and Architecture to align ML/AI infrastructure with enterprise standards; Manage CI/CD pipelines for model deployment, automated testing, and infrastructure-as-code; Monitor model performance, stability, latency, and data quality across production systems; Ensure all deployed AI/ML models comply with Model Risk Management guidelines and regulatory expectations; Evaluate and integrate emerging MLOps/AIOps tools and capabilities; Lead PoCs and pilot initiatives focused on scalable AI automation

Requirements

Bachelor’s Degree in Computer Science, Engineering, Data Science, or related fields; 4–6+ years in Machine Learning Engineering, MLOps, AIOps, or related roles; Experience supporting Data Scientists with model operationalization and deployment; Strong background managing production AI systems, including LLMs, RAG pipelines, and predictive models; Experience with Azure, Kubernetes, Docker, MLflow, Databricks, CI/CD, and model monitoring tools; Adopting Practical Approaches; Articulating Information; Challenging Ideas; Developing Expertise; Documenting Facts; Embracing Change; Interpreting Data; Managing Tasks; Big Data Frameworks and Tools; Data Engineering; Data Integrity; IT Knowledge; Stakeholder Management (IT)

Nice to have

Master’s Degree; certifications in Azure ML; certifications in AWS ML; certifications in Kubernetes; certifications in MLOps; certifications in DevOps; certifications in Cloud Engineering