AI Platform Engineer
Core
Build and operate the machine learning and generative AI platform for the Cancer Diagnostics division, owning the full model lifecycle from data pipelines to production serving and monitoring.
Role type
Senior IC AI Platform Engineer
Builds
Production ML and LLM inference platforms, data/feature pipelines, and model lifecycle automation tools
Domain
Healthcare diagnostics + MLOps infrastructure
Deliverable
production ML models | infrastructure
Required skills
Python, Kubernetes, CI/CD, GitOps, distributed training, model serving, GPU infrastructure management, automated evaluation gates, model registry/versioning, API/SDK development
Preferred skills
ML workflow orchestration (Kubeflow, Airflow), GPU optimization (TensorRT, ONNX), feature stores, progressive delivery (canary, A/B), model drift detection, regulated environment deployment (HIPAA, GxP), Go/Java
Technologies
Kubernetes, AWS, Python, Kubeflow, Argo Workflows, MLflow, TensorRT, ONNX Runtime, Knative, KEDA
Responsibilities
Build data and feature pipelines for ML/LLM workloads; Implement automated evaluation and promotion gates; Automate model lifecycle via CI/CD and GitOps; Operate production model-serving infrastructure; Architect and manage GPU infrastructure; Instrument platform for logging, telemetry, and drift detection; Extend model registries and metadata systems; Build developer-facing APIs and SDKs
Seniority
Senior, hands-on IC
