Principal AI Operations Engineer

• Compensation: USD 141,500 - USD 268,500 - yearly

About Abb Vie

Abb Vie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about Abb Vie, please visit us at  .

Follow @abbvie on Linked In, Facebook , Instagram , X and You Tube.

Come to work each day with an inclusive and collaborative business technology team. As a Principal AI Operations Engineer in Abb Vie Business Technology Solutions (BTS), 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.

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.

Responsibilities:

• Architect patterns that increase success in getting AI delivery teams to ship AI and ML models to solve business problems.
• 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 up 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.
• Initiate and drive projects with minimal oversight and guidance.
• Tools and skills you will use in this role:
  • AI platforms like Sage Maker, Databricks, etc.
  • CICD Tools like Git Hub Actions
  • Infrastructure-as-Code tools like Terraform
  • Lakehouse data storage patterns like Iceberg and Delta.
  • JIRA, CI/CD and Agile project methodology
  • Cloud environment (AWS, Azure, etc.) with large datasets and with streaming data architectures.
  • Large Language Models and Generative AI
  • ML Registries like MLFlow

Required:

• Bachelor's Degree with 9 years of experience;
  Master's Degree with 8 years of experience;
  PhD with 4 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 architecting with advanced analytics and data science platforms.
• Respective years of experience with data lakes like Iceberg or Delta.
• 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.
• 3+ years of experience in developing and deploying solutions in a Cloud environment (AWS, Azure) with large datasets and with streaming data architectures.
• 3+ years of experience in using MLflow for model registry, experiment tracking, and model validation.

Preferred:

• Experience with Pharma data, including insights into commercial sales and field operations is a plus.
• Consulting experience in ML/AI Engineering or Ai Platform domain.
• 5+ years of working experience in ML/AI Engineering, Data Science, or AI Platform engineering
• 5+ years of experience in advanced SQL, Python, Spark, and a broad array of ML frameworks
• 5+ years of experience architecting with advanced analytics and data science platforms.
• 5+ years of experience with data lakes like Iceberg or Delta.
• Self-starter, comfortable with ambiguity, experience initiating and driving projects with minimal oversight and guidance.

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state orlocal law:

• The compensation range described below is the range of possible base pay compensation that the Company believes ingood faith it will pay for this role at the timeof this posting based on the job grade for this position.
  
  Individual compensation paid within this range will depend on many factors including geographic location, andwemayultimatelypaymore or less than the posted range. This range may bemodifiedin thefuture.
• We offer a comprehensive…