Apply now: MLOps Engineer, Location is Remote. The start date is August 25, 2025, or ASAP for this 3.5-month contract role with potential extension.
Job Title: MLOps Engineer
Location-Type: Remote
Start Date Is: August 25, 2025, or ASAP
Duration: 3.5 months (Contract, potential extension)
Compensation Range: $55.00/hr – $65.00/hr W2
Job Description:
We are seeking an MLOps Engineer to design, implement, and manage infrastructure for deploying and maintaining machine learning models in production. This role sits at the intersection of Data Science, Data Engineering, and DevOps , requiring expertise in cloud platforms, automation, and ML lifecycle management .
Day-to-Day Responsibilities:
Design and deploy scalable ML infrastructure using cloud and containerization (Azure, AKS, Kubernetes, Docker).
Build CI/CD pipelines for model deployment, monitoring, and retraining.
Collaborate with Data Scientists and Engineers to implement model validation and testing procedures .
Optimize and refactor ML development code for production readiness.
Develop data and feature engineering pipelines to support models.
Configure and automate environment builds in production.
Ensure scalability, reliability, and continuous enhancement of ML systems.
Requirements:
Must-Haves:
Strong experience with Kubernetes, AKS, and Azure Cloud .
Hands-on expertise with Azure DevOps and Databricks .
Proven experience in building and managing ML infrastructure .
Familiarity with CI/CD for ML model deployment .
Ability to collaborate with cross-functional teams in a fast-paced environment.
Nice-to-Haves:
MLOps or ML infrastructure deployment experience.
Exposure to advanced ML lifecycle automation frameworks.
Knowledge of monitoring and retraining pipelines for AI/ML models.
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