Description

You will design, build, and maintain MLOps pipelines and cloud solutions for machine learning models.

This role is on-site.

Responsibilities

• Design and implement cloud solutions and MLOps pipelines on AWS.
• Build and manage inference systems using advanced deployment methods.
• Implement CI/CD practices and DevOps principles using Git, GitHub, and Azure DevOps.
• Containerize applications and orchestrate systems with Docker and Kubernetes.
• Translate higher-level requirements into user stories and tasks.

Required Skills

• 9+ years of experience (or 6+ years with a Master's degree).
• Proficiency in Python, Golang, Java, or C/C++.
• Experience with MLOps frameworks such as MLflow and Kubeflow.
• Strong programming skills in Python, R, or SQL.
• Experience with containerization (Docker) and Kubernetes.
• Familiarity with CI/CD tools including Git, GitHub, and jFrog Artifactory.
• Strong communication and collaboration abilities.

Preferred Skills

• Knowledge of inference systems like Seldon or Kubeflow.
• Experience deploying applications with Helm, Helmfile, CloudFormation, or Terraform.
• Exposure to observability tools such as Evidently AI.

Key Skills

Education

Bachelor's or Master's degrees