ML Platform Engineer — Production AI/LLM Infra

Abbott Laboratories; Madison (WI); On-site; USD 61,000 - 123,000; Full time

Job summary

Abbott is seeking an AI Platform Engineer to build and operate the ML and generative AI platform used across Cancer Diagnostics. You will own the full model lifecycle in production—from data pipelines to serving and monitoring—while delivering robust, auditable platform services.

You will implement automated evaluation gates, enable CI/CD and GitOps pipelines, and scale GPU infrastructure for training and inference.

Qualifications

• Bachelor's degree in Computer Science, Engineering, AI/ML, or related field.
• 3+ years building and operating production software, incl. ML/AI infra.
• Strong Python and software engineering fundamentals (testing, code reviews).
• Experience with ML model lifecycle: training, evaluation, deployment, monitoring, retraining.
• Kubernetes experience—deploying, scaling, debugging containerized workloads on a major cloud provider (AWS preferred).
• Experience with CI/CD, GitOps-based delivery, and infrastructure automation.

Responsibilities

• Build and maintain data, feature, and training pipelines for ML/LLM workloads.
• Implement automated evaluation and promotion gates for models.
• Automate the model lifecycle end-to-end via CI/CD and GitOps.
• Operate production model-serving infra with low latency and autoscaling.

Skills

Python

Kubernetes

CI/CD

GitOps

ML Platform

Education

Bachelor's degree in CS/Engineering/AI/ML

Tools

Kubeflow

Argo Workflows

Airflow

MLflow

Weights & Biases

Job description

Abbott is seeking an AI Platform Engineer to build and operate the ML and generative AI platform used across Cancer Diagnostics. You will own the full model lifecycle in production—from data pipelines to serving and monitoring—while delivering robust, auditable platform services.

You will implement automated evaluation gates, enable CI/CD and GitOps pipelines, and scale GPU infrastructure for training and inference.