Machine Learning /AI Engineer

Skills

• Design and develop Generative AI platforms based on microservices and event-driven architectures. • Write clean efficient and maintainable code in Python with additional experience in Go and/or TypeScript being a plus. • Implement the fundamental building blocks along with working examples to deliver the platform-level capabilities as planned. • Build deploy and manage Cloud-native Machine Learning applications using Docker Kubernetes and Terraform. • Collaborate with Data Scientists to integrate Machine Learning models and the run-time dependencies into the platform. • Work with Domain Application team to help on-boarding troubleshooting customization and enhancements. • Conduct testing activities to meet various security compliance and technical standards in the bank.

Description

As a Generative AI (GenAI) Platform Engineer, you will be responsible for designing, developing, and operate our internal GenAI platform that will enable U. S. Bank developers to rapidly launch GenAI-enabled services for the customers. You will work closely with Data Science, Data Engineering and MLOps teams, and other stakeholders to ensure the platform is feature-rich, secure, robust, scalable. Your expertise in machine learning engineering (especially in GenAI), platform development, and cloud technologies will be crucial in driving our projects forward.

Responsibilities

• • Highly proficient in at least one of the programming languages, preferably in Python, Go, TypeScript or Scala/Java.
• • Expertise in Machine Learning application development or platform engineering.
• • Experience in Containerization and IAC (Infra as Code) technologies with at least one of the major Cloud providers.
• • Good understanding of data science and machine learning principles.
• • Deep understanding on LLM (Large Language Models) and RAG (Retrieval-Augmented Generation) concepts.
• • Hands-on experience in building LLM/RAG applications is highly preferred.
• • Good understanding of security protocols, including TLS, SSH.
• • Familiarity with distributed data systems such as Kafka, Spark, ELK.
• • Workable experience with the CI/CD, DevOps and SRE tool chains.