Senior AI/ML Platform Engineer - MLOps & Cloud Infra

MACHINE LEARNING TECHNOLOGIES LLC; Linthicum (MD); On-site; USD 150,000 - 210,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC in Linthicum Heights, MD seeks a Senior AI/ML Platform Engineer to design, implement, and run the enterprise AI/ML platform. You will drive platform automation, MLOps, CI/CD, cloud infrastructure, and cost optimization while ensuring reliability and observability at production scale.

Required: 10+ years in platform/MLOps, strong Python, Kubernetes, cloud experience, and proficiency with Terraform/Ansible. Prior ML lifecycle and deployment experience is essential.

Qualifications

• 10+ years in platform/MLOps or data/software engineering.
• Bachelor's degree (Master's preferred).
• Strong Python production-grade software development.
• Experience designing ML CI/CD pipelines and deployment processes.
• Hands-on with AWS/Azure/GCP and cost optimization.
• Advanced Kubernetes experience.
• Observability tools: Prometheus, Grafana, Datadog, OpenTelemetry.
• Production-scale Terraform and Ansible.
• ML lifecycle: tracking, registries, feature stores, drift monitoring.
• Automated model validation, A/B testing, canary deployments, rollbacks.

Responsibilities

• Design, implement, operate, and continuously improve the shared enterprise AI/ML platform.
• Advance platform automation, MLOps, CI/CD, cloud infra, and observability.

Skills

Python

MLOps

CI/CD

Cloud platforms

Kubernetes

Observability

Terraform

Ansible

ML lifecycle

Model serving

Education

Bachelor's degree in CS/IS/Engineering/related

Master's degree preferred

Tools

Prometheus

Grafana

Datadog

OpenTelemetry

Terraform

Ansible

Job description

MACHINE LEARNING TECHNOLOGIES LLC in Linthicum Heights, MD seeks a Senior AI/ML Platform Engineer to design, implement, and run the enterprise AI/ML platform. You will drive platform automation, MLOps, CI/CD, cloud infrastructure, and cost optimization while ensuring reliability and observability at production scale.

Required: 10+ years in platform/MLOps, strong Python, Kubernetes, cloud experience, and proficiency with Terraform/Ansible. Prior ML lifecycle and deployment experience is essential.