
Senior MLOps Engineer
6 days ago
Job Overview:
We're seeking a skilled MLOps Engineer to bridge the gap between data science and DevOps, ensuring ML workflows are robust, scalable, and secure across cloud and on-prem environments.
Responsibilities:
- Collaborate with Data Scientists and Engineers to build and automate ML pipelines (training, validation, deployment, monitoring)
- Develop and maintain CI/CD pipelines tailored for ML model lifecycle
- Containerize ML models using Docker and orchestrate deployment with Kubernetes
- Implement model versioning, drift detection, monitoring, and rollback strategies
- Integrate ML pipelines with data versioning tools (DVC, MLflow, Weights & Biases, etc.)
Requirements:
- Strong experience with MLOps tools and frameworks (MLflow, Kubeflow, Airflow, TFX, etc.)
- Experience with CI/CD tools (GitLab CI/CD, Jenkins, CircleCI, etc.)
- Proficiency in Docker, Kubernetes, and container orchestration
- Solid Python programming skills and familiarity with ML libraries (scikit-learn, TensorFlow, PyTorch)
Qualifications:
- Bachelors/Masters in Computer Science, Data Engineering, or related field
- Experience working with GPU/TPU-enabled training environments
- Exposure to feature stores, data lineage, and model governance frameworks
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