Remote Principal ML Platform Engineer

PointClickCare; Santa Cruz de Tenerife; À distance; EUR 174 000 - 194 000; Plein temps

Résumé du poste

PointClickCare seeks a Principal AI Machine Learning Platform Engineer to set the technical vision and strategy for the ML platform powering ML and generative AI across the company. You will define reference architectures, standards, and roadmaps for pipelines, tooling, and infrastructure used for model training, deployment, serving, and monitoring, and mentor teams to raise engineering bar.

Lead security, reliability, observability, and cost-efficient integration while guiding cross-team

Qualifications

• Expert level in Python and Java with strong software engineering fundamentals.
• Deep experience designing and building ML platforms and ML Ops workflows at scale.
• Extensive experience with cloud platforms (AWS, Azure, and/or GCP), containerization, and orchestration (Docker, Kubernetes).
• Demonstrated track record of setting technical direction across multiple teams.

Responsabilités

• Translate business and product objectives into a multi-quarter technical strategy and roadmap for the ML platform.
• Define architectures and standards for scalable data and ML pipelines for model training, deployment, and serving.
• Set direction for MLOps including CI/CD for models, model registry, feature stores, and experiment tracking.
• Establish reliability, observability, and performance practices for ML systems in production.
• Define secure architecture for ML platform including RBAC and audit logging.
• Provide technical leadership and mentorship across engineering teams.

Connaissances

Python

Java

ML platform design

MLOps

Cloud platforms

Kubernetes

Formation

Bachelor’s degree or higher in Computer Science or related field

Outils

MLFlow

Kubeflow

Ray

Docker

Kubernetes

Description du poste

PointClickCare seeks a Principal AI Machine Learning Platform Engineer to set the technical vision and strategy for the ML platform powering ML and generative AI across the company. You will define reference architectures, standards, and roadmaps for pipelines, tooling, and infrastructure used for model training, deployment, serving, and monitoring, and mentor teams to raise engineering bar.

Lead security, reliability, observability, and cost-efficient integration while guiding cross-team