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MLOps / AI Ops Engineer

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Onsite

MLOps / AI Ops Engineer

DeWinter Group

MLOps / AI Ops Engineer

Skills

PythonJenkinsMachine LearningAIGitHubKubernetes

2 months ago

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Important information


Contract type:

Freelance / Contract

Location:

Campbell, CA, USA

Work mode:

Onsite

Published on:

30 August 2026

What they need


Title: MLOps / AI Ops Engineer

Job Type: Contract

Contract Length: 12 Months

Pay Range: $50/hr – $175/hr

Start Date: ASAP

Location: Remote

About The Opportunity Our client, a leader in AI testing and Generative AI solutions, is looking for a skilled MLOps / AI Ops Engineer to join their team for a 12-month engagement. This project involves building and automating end-to-end CI/CD pipelines for machine learning models and establishing production observability frameworks to ensure model reliability and scalability. This is a high-impact role that requires a self-motivated professional who can hit the ground running and deliver results quickly.

Key Responsibilities & Deliverables This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:

  • Building and automating end-to-end CI/CD pipelines for machine learning models.
  • Setting up observability and monitoring frameworks to track model accuracy, latency, and drift in real-time.
  • Managing model deployment strategies (canary, A/B testing) to ensure zero-downtime updates.
  • Automating the scaling of inference services based on incoming request volume.
  • Establishing standard workflows for model governance and reproducibility.

Required Skills & Experience: We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have:

  • 4+ years of experience in MLOps or DevOps with an ML focus.
  • Deep expertise in MLflow, Kubeflow, and CI/CD tools (GitHub Actions, Jenkins). This isn't a learning role—you need to be a subject matter expert.
  • Demonstrated ability to work autonomously and manage your own time effectively to meet project goals.
  • Experience with Python, Kubernetes, and cloud-native ML services.
  • Strong communication skills to provide clear and concise status updates to the project team.

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