ML Platform Engineer for Scalable AI in Healthcare

Thornton Tomasetti; Madison (WI); On-site; USD 61,000 - 123,000; Full time

Job summary

Abbott is seeking an AI Platform Engineer to own the full model lifecycle from data pipelines to production serving for cancer diagnostics. You will build and operate the ML platform that enables teams to train, evaluate, deploy, and monitor models with low latency and scalable GPU infrastructure.

You will implement automated evaluation gates, promote models through CI/CD, and extend registries and APIs for self-service platform usage.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 3+ years building and operating production software including ML/AI infrastructure.
• Strong Python, including software engineering fundamentals—testing, code review, and readable code.
• Experience with the ML model lifecycle: pipelines from training through evaluation, deployment, monitoring, and retraining.
• Kubernetes experience—deploying, scaling, and debugging containerized workloads on AWS or major cloud provider.
• Experience with CI/CD, GitOps-based delivery, and infrastructure automation.

Responsibilities

• Build and maintain data, feature, and training pipelines for ML and LLM workloads—ingestion, transformation, fine-tuning, distributed training, and reproducible experiment execution with lineage tracked from dataset and code to resulting model.
• Implement automated evaluation and promotion gates—performance benchmarks, regression checks, and validation criteria for production.
• Automate the model lifecycle end to end via CI/CD and GitOps: packaging, promotion across environments, progressive rollout, and rollback.
• Build and operate production model-serving infrastructure for LLMs and predictive models, including inference optimization, autoscaling, and low-latency serving across formats/runtimes.
• Architect and manage GPU infrastructure—scheduling, autoscaling, resource isolation, and utilization efficiency for training and inference.

Skills

Python programming

CI/CD practices

Go/Java

Kubernetes experience

Education

Bachelor's degree in Computer Science, Engineering, AI/ML, or related field

Tools

Kubeflow

Argo Workflows

Airflow

MLflow

Weights & Biases

ONNX Runtime

TensorRT

Knative

KEDA

Job description

Abbott is seeking an AI Platform Engineer to own the full model lifecycle from data pipelines to production serving for cancer diagnostics. You will build and operate the ML platform that enables teams to train, evaluate, deploy, and monitor models with low latency and scalable GPU infrastructure.

You will implement automated evaluation gates, promote models through CI/CD, and extend registries and APIs for self-service platform usage.