MLOps Engineer
3 days ago
What You'll Be Doing
- Automate and orchestrate ML pipelines for training, testing, and deployment.
- Implement CI/CD practices specific to machine learning workflows.
- Monitor and manage production ML models for performance, drift, and accuracy.
- Collaborate with data scientists to transition models from research to production-ready systems.
- Ensure scalability, reliability, and security of the ML infrastructure.
What We'd Love To See
- 3–5 years of experience in MLOps, DevOps, or a similar role.
- Strong expertise in containerization (Docker, Kubernetes) and cloud platforms (AWS, Azure, GCP).
- Proficiency in scripting languages like Python and knowledge of ML frameworks (TensorFlow, PyTorch).
- Experience with MLOps tools like MLflow, Kubeflow, or Sagemaker.
- Solid understanding of CI/CD tools such as Jenkins, GitLab, or GitHub Actions.
It'd Be Great If You Had
- Experience with monitoring tools like Prometheus and Grafana.
- Knowledge of big data technologies like Spark or Hadoop.
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