This role pays less than
99%
of similar roles. Most pay
$151,000–$214,000
— the shaded band above.
At the midpoint, this role pays about
$92k
versus about
$182k
for comparable roles.
Based on 240 similar postings.
Employer
About Abbott
Abbott Laboratories is a global healthcare company that manufactures and markets a broad and diversified line of health care products including diagnostics, medical devices, nutritionals, and branded generic pharmaceuticals. Industry: Healthcare & Medical Devices
Abbott currently has
90 open roles
on FindRole.
Listed pay typically runs
$99,300–$198,700
across 89 roles with salary data.
The AI Platform Engineer joins the Abbott Cancer Diagnostics team to build and operate a machine learning and generative AI platform. This role involves managing the full model lifecycle, including data and feature pipelines, training, evaluation, serving, and monitoring for LLM and predictive models. The engineer will develop infrastructure for inference optimization, GPU management, and automated CI/CD and GitOps workflows to ensure reproducible experiments and auditable deployments. Key technical requirements include proficiency in Python, Kubernetes, and experience with cloud providers like AWS. Candidates should possess skills in ML workflow orchestration tools such as Kubeflow or Airflow, and knowledge of technologies like ONNX Runtime or TensorRT. The role focuses on solving complex infrastructure challenges within the cancer diagnostics domain to ensure that software supporting patient care is reliable, scalable, and compliant with regulated environments.
Machine Learning
Natural Language Processing
Generative AI
Large Language Models
Python
RAG
Batch and Stream Processing
Model Distillation
Agile
SAFe
Cloud Platforms
AWS
Kubernetes
Docker
Terraform
CloudFormation
Python
CI/CD
Infrastructure as Code
MLOps
Amazon Bedrock
SageMaker
DevSecOps
RMF
Platform One
Iron Bank
Big Bang
FedRAMP
IL5