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MLOps Engineer

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Remote

MLOps Engineer

developrec

MLOps Engineer

Skills

DockerPythonGitLabGrafanaMachine LearningAIAWSPrometheusGitHubKubernetesTerraformAzure

7 days ago

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Important information


Contract type:

Freelance / Contract

Location:

United States

Work mode:

Remote

Published on:

15 October 2026

What they need


Develop are looking for an experienced Senior MLOps Engineer to support the development, deployment and optimisation of production-grade Machine Learning infrastructure within a large-scale enterprise environment.

This is a hands-on engineering role focused on building scalable ML platforms, automating model deployment and improving the reliability and performance of machine learning systems.

Key Responsibilities:

  • Design, build and maintain scalable MLOps pipelines and infrastructure.
  • Develop automated CI/CD pipelines for machine learning model training, testing and deployment.
  • Deploy and manage ML models in production environments.
  • Implement model monitoring, versioning, experiment tracking and performance optimisation.
  • Build and maintain containerised ML workloads using Docker and Kubernetes.
  • Work closely with Data Scientists, ML Engineers and Platform Engineering teams.
  • Implement Infrastructure as Code (IaC) and automated cloud provisioning.
  • Improve model lifecycle management, observability and platform reliability.

Essential Technical Skills:

  • Strong commercial experience in MLOps or ML Platform Engineering.
  • Advanced Python programming skills.
  • Hands-on experience with MLflow, Kubeflow or similar MLOps frameworks .
  • Strong knowledge of Docker and Kubernetes .
  • Experience building CI/CD pipelines using GitHub Actions, GitLab CI or Azure DevOps .
  • Cloud experience with AWS SageMaker, Azure Machine Learning or Google Vertex AI .
  • Infrastructure as Code using Terraform .
  • Experience with model serving, monitoring and automated retraining pipelines.
  • Understanding of ML model lifecycle management, feature stores and data pipelines.

Desirable Experience:

  • LLMOps and deployment of Generative AI models.
  • Model serving frameworks such as KServe, BentoML or NVIDIA Triton.
  • Distributed model training and inference.
  • Monitoring tools such as Prometheus and Grafana.

Contract Details:

  • Position: Senior MLOps Engineer
  • Contract Type: B2B / Freelance
  • Duration: 12 months
  • Location: 100% Remote, Europe
  • Language: English
  • Start Date: ASAP

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