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MLOps Engineer
3 weeks ago
Job Description :
- Experience in CI/CD pipelines, scripting languages, and a deep understanding of version control systems (e.g. Git), containerization (e.g. Docker), and continuous integration/deployment tools (e.g. Jenkins) third party integration is a plus, cloud computing platforms (e.g. AWS, GCP, Azure), Kubernetes and Kafka.
- Experience in 4+ years of experience building production-grade ML pipelines.
- Proficient in Python and frameworks like Tensorflow, Keras, or PyTorch.
- Experience with cloud build, deployment, and orchestration tools
- Experience with MLOps tools such as MLFlow, Kubeflow, Weights & Biases, AWS Sagemaker, Vertex AI, DVC, Airflow, Prefect, etc.,
- Experience in statistical modeling, machine learning, data mining, and unstructured data analytics.
- Understanding of ML Lifecycle, MLOps & Hands on experience to Productionize the ML Model
- Detail-oriented, with the ability to work both independently and collaboratively.
- Ability to work successfully with multi-functional teams, principals, and architects, across organizational boundaries and geographies.
- Equal comfort driving low-level technical implementation and high-level architecture evolution
- Experience working with data engineering pipelines.
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MLOps Engineer
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