Machine Learning Engineer

🚀Position 1

Location

Contract

Start Date

🔎 Role Overview

proficient MLOps Engineer (Level II)

🎯 Responsibilities

• Deploy and maintain ML models in production (AWS SageMaker, MLflow, Kubeflow).
• Manage CI/CD pipelines and infrastructure as code (Terraform, ArgoCD).
• Support ETL/data workflows using Airflow or Astronomer.
• Collaborate with data scientists to transition models into production environments.
• Troubleshoot issues, perform root cause analysis, and drive remediation.

🛠 Qualifications

• 2–4 years of experience in

  MLOps or DevOps

  .
• Strong Python skills for automation & workflow management.
• Hands-on with cloud ML tools and orchestration frameworks.
• Familiarity with CI/CD and monitoring best practices.

🚀 Position 2

Location

Contract

Start Date

🔎 Role Overview

Senior MLOps Engineer (Level III)

Responsibilities

• Lead design of

  scalable MLOps frameworks

  and automation strategies.
• Build and optimize monitoring/alerting systems for

  drift, accuracy, and latency

  .
• Manage governance and versioning with GitHub Enterprise and JFrog Artifactory.
• Enhance deployment/retraining pipelines (Terraform, ArgoCD).
• Partner with Big Data and Work Routing teams for system reliability.
• Mentor junior engineers and lead

  knowledge transfer sessions

  .

Qualifications

• 4–6 years of experience in

  MLOps, DevOps, or ML Engineering

  .
• Advanced proficiency in automation, pipelines, and

  hybrid infra (on-prem + cloud)

  .
• Hands-on expertise with Terraform, ArgoCD, and orchestration tools.
• Strong leadership and communication skills.

Why Join?

• Be part of an

  INSPYR Solutions Managed Service team

  .
• Work on cutting-edge

  production ML infrastructure

  .

• Fast selection

  : one interview with the hiring manager.
• Opportunity to contribute to a

  long-term, high-impact engagement

  .