Senior AI Operations Engineer

Role Overview

As a Senior AI Operations Engineer at AbbVie, you will have opportunities to contribute to the digital transformation of a leading biopharma company, helping to create solutions that impact patients and their communities for the better. You will be part of a collaborative business technology team and will have the opportunity to work with cross-functional teams to deliver and execute complex analytics problems.

What You Will Do

Develop and configure model registries and experiment tracking, set-up model drift detection and observability patterns, create reusable templates and patterns for rapidly creating projects, create central CICD workflows across ML and AI projects, set-up and use Feature Stores and online feature serving, design cloud architecture to solve ML and AI problems, enforce code quality standards, data quality and ensure reproducibility and compliance.

Why It Might Be a Fit

A successful candidate will bring best-in-class AI/ML Engineering and Operations methodologies, deep understanding of AI/ML Platform space, proven history of solving operationalizing ML and AI and ability to work with cross-functional teams to deliver and execute complex analytics problems.

Requirements

• Bachelor’s Degree with 7 years of experience; Master’s Degree with 6 years of experience; PhD with 2 years of experience.
• Respective years of working experience in doing ML/AI Engineering, Data Science, or AI Platform engineering.
• Respective years of experience in advanced SQL, Python, Spark, and a broad array of ML frameworks.
• Respective years of experience with advanced analytics and data science platforms like Databricks OR Sagemaker.
• Respective years of experience with CI/CD like GitHub Actions.
• Respective years of experience with Infrastructure-as-Code tools like Terraform
• Respective years of experience with data lakes like Iceberg or Delta.
• Respective years of experience in developing and deploying solutions in a Cloud environment (AWS, Azure) with large datasets and with streaming data architectures.
• Respective years of experience in using MLflow for model registry, experiment tracking, and model validation.
• Minimum 2 years of experience with GenAI application development, LLM prompt engineering, LLM-based solution architecture like RAG, developing Chatbots and AI agents using both unstructured and structured data.
• Self-starter, comfortable with ambiguity, experience in initiating and driving projects with minimal oversight and guidance.

Benefits

• paid time off (vacation, holidays, sick)
• medical/dental/vision insurance
• 401(k)
• long-term incentive programs

Tagged as: Python, SQL