Job Description
Job Description
- 5+ years of good experience in MLOps.
- A talented MLOps Engineer help operationalize machine learning models at scale.
- The ideal candidate will have a strong background in machine learning, software engineering, and DevOps practices, with expertise in deploying, monitoring, and maintaining ML models in production environments.
- Strong experience in MLOps, DevOps, or related fields.
- Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.Hands-on experience with cloud platforms (e.g., AWS, GCP, or Azure) and their ML services.
- Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).
- Experience with CI/CD tools (e.g.GitHub Actions orJenkins).
- Familiarity with monitoring tools for ML models (e.g., Dynatrace, Prometheus, Grafana, or MLFlow).
- Strong understanding of version control for models and data (e.g., Git).
- Knowledge in scripting using python/unix bash...
- 5+ years of good experience in MLOps.
- A talented MLOps Engineer help operationalize machine learning models at scale.
- The ideal candidate will have a strong background in machine learning, software engineering, and DevOps practices, with expertise in deploying, monitoring, and maintaining ML models in production environments.
- Strong experience in MLOps, DevOps, or related fields.
- Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.Hands-on experience with cloud platforms (e.g., AWS, GCP, or Azure) and their ML services.
- Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).
- Experience with CI/CD tools (e.g.GitHub Actions orJenkins).
- Familiarity with monitoring tools for ML models (e.g., Dynatrace, Prometheus, Grafana, or MLFlow).
- Strong understanding of version control for models and data (e.g., Git).
- Knowledge in scripting using python/unix bash...
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