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Senior AI/ML Platform Engineer (MLOps & Cloud Infrastructure)
Visa Sponsorship
AI Summary
Design, implement, and optimize a scalable enterprise AI/ML platform with a focus on automation, MLOps, and cloud infrastructure. Lead CI/CD pipelines, Kubernetes, observability, and cost optimization while ensuring reliability and governance. Requires 10+ years of platform engineering experience with 2+ years in production ML systems.
Key Highlights
Lead design, implementation, and continuous improvement of a shared AI/ML platform
Focus on MLOps, CI/CD, cloud infrastructure (AWS/Azure/GCP), and cost optimization
Advanced Kubernetes, Terraform, and observability tools (Prometheus, Grafana, Datadog)
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Key Responsibilities
Design and implement scalable AI/ML platform architectures for enterprise use
Develop and maintain MLOps pipelines, CI/CD workflows, and automation frameworks
Manage cloud infrastructure (AWS/Azure/GCP) with a focus on cost optimization and reliability
Ensure observability, monitoring, and incident response for production ML systems
Implement and enforce ML lifecycle best practices, including model serving, drift monitoring, and validation
Develop internal SDKs, CLI tools, and reusable deployment templates for platform users
Collaborate with cross-functional teams to integrate AI/ML solutions into production environments
Technical Skills Required
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Nice to Have
Experience with Internal Developer Platforms (IDPs)
LLM serving technologies (e.g., vLLM, TGI)
Government/regulated environments (e.g., FedRAMP compliance)
NIST AI Risk Management Framework knowledge
FinOps practices and tools (e.g., Infracost, AWS Cost Explorer)
Job Description
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