AI Platform Engineer

Abbott seeks an AI Platform Engineer to build and operate machine learning and generative AI infrastructure for cancer diagnostics. The role encompasses the full model lifecycle—from data pipelines and training through production serving, monitoring, and retraining—with emphasis on platform reliability, auditability, and developer experience.

Responsibilities

• Build and maintain data, feature, and training pipelines with lineage tracking for ML and LLM workloads
• Implement automated evaluation gates and promotion criteria to advance models toward production
• Automate full model lifecycle through CI/CD and GitOps, including packaging, deployment, and rollback
• Build and operate production model-serving infrastructure with optimization, autoscaling, and low-latency serving
• Architect and manage GPU infrastructure for training and inference, including scheduling and resource isolation

Requirements

• Bachelor's degree in Computer Science, Engineering, AI/ML, or equivalent practical experience
• 3+ years building and operating production software with significant ML or AI infrastructure work
• Strong Python with software engineering fundamentals: testing, code review, and maintainable design
• End-to-end ML model lifecycle experience: training, evaluation, deployment, monitoring, retraining
• Kubernetes deployment and scaling on major cloud provider (AWS preferred)
• CI/CD, GitOps-based delivery, and infrastructure automation experience

Compensation: $61,300–$122,700 base