Related skills
aws kubernetes tensorflow pytorch mlops📋 Description
- Define the MLOps vision and long-term strategy.
- Own the end-to-end ML production platform.
- Align infra investments with real-time personalization goals.
- Lead build vs buy decisions for cloud tools.
- Ensure scalable, reliable ML services at scale.
- Manage GPU/cloud compute governance and costs.
🎯 Requirements
- 10+ years in ML Infrastructure/MLOps or data platform leadership.
- Proven track record scaling MLOps across model lifecycle.
- AWS-based cloud infra + Kubernetes (EKS), Docker, IaC (Terraform/Pulumi).
- Hands-on with PyTorch, TensorFlow, Kubeflow, SageMaker.
- Expertise in Feature Stores and high-throughput pipelines (Spark, Flink, Kafka).
- Partner with AI Research/Data Science; CI/CD for ML incl tests and canaries.
🎁 Benefits
- Equal opportunity employer.
- Reasonable accommodations available.
- Culture of psychological safety and candor.
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