Senior AI Operations Engineer

About AbbVie

AbbVie'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 AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

Come to work each day with an inclusive and collaborative business technology team. As a Data Scientist in AbbVie 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:

• 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.
• Initiate and drive projects with minimal oversight and guidance.
• Tools and skills you will use in this role:
  • AI platforms like Databricks or SageMaker
  • CICD Tools like GitHub 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) with large datasets and with streaming data architectures.
  • Large Language Models and Generative AI
  • ML Registries like MLFlow

Required:

• 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.

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.
• 3+ years of experience with advanced analytics and data science platforms like Databricks.
• 3+ years of experience with data lakes like Iceberg or Delta.
• 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.

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

• The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.
• We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
• This job is eligible to participate in our long-term incentive programs.

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

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https://www.abbvie.com/join-us/reasonable-accommodations.html