AI/ML Platform Engineer

Role Overview

• Collaborating closely with various business units, we provide strategic advice, prototype solutions, and develop and manage software applications tailored for internal use.
• Building Internal platform tools and services: self-service portals/workbenches, backend APIs (Python/FastAPI), automations and CI/CD tooling.
• Cloud infrastructure & troubleshooting (weekly) Writing and maintaining Terraform; provisioning and configuring platform resources across AWS and Azure.
• Helping teams productionize models—hosting options, inference patterns, scaling, cost, and operational readiness across SageMaker, Bedrock, Azure ML/AI Foundry, and Kubernetes.

Requirements

• Four-year or Graduate Degree in Computer Science, Statistics, Mathematics, Data Science, or any other related discipline or commensurate work experience or demonstrated competence.
• Typically has 7-10 years of work experience, preferably in computer programming languages, machine learning, algorithms, statistical methods, or a related field.
• AWS Certified Machine Learning Specialty

Tech Stack

• AWS
• Azure
• Cloud
• Kubernetes
• Python
• Terraform

Benefits

• Health insurance
• Dental insurance
• Vision insurance
• Long term/short term disability insurance
• Employee assistance program
• Flexible spending account
• Life insurance
• Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure
• 11 paid holidays
• Additional flexible paid vacation and sick leave