Senior MLOps Engineer
We are seeking a Senior MLOps Engineerwith proven experience in building and scaling machine learning operations in production environments. The ideal candidate must have strong hands-on expertise with Databricks and MLflow, as these are core requirements for the role.
What you will do
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Build, automate, and maintain end-to-end ML pipelines
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Deploy, monitor, and optimize machine learning models in production
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Manage experiment tracking, model registry, and lifecycle workflows using MLflow
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Collaborate with data scientists, data engineers, and software teams to productionize ML solutions
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Improve the reliability, scalability, and governance of ML platforms
What we are looking for
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5+ years of experience in MLOps, Machine Learning Engineering, or similar roles
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Mandatory hands-on experience with Databricks and MLflow
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Strong Python skills and experience working with cloud-based environments
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Solid understanding of CI/CD, automation, model deployment, and monitoring
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Ability to work cross-functionally and communicate clearly with technical and non-technical stakeholders
Nice to have
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Experience with orchestration and infrastructure tools such as Airflow, Docker, Kubernetes, or Terraform
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Familiarity with AWS, Azure, or GCP
