MACHINE LEARNING ENGINEER
1 day ago
Job Title: Machine Learning Engineer
About the Role:
We are seeking a highly skilled and motivated Machine Learning Engineer to join our team. The ideal candidate will be responsible for streamlining the deployment, scaling, and monitoring of machine learning models in production.
Key Responsibilities:
- Design and implement end-to-end machine learning infrastructure and workflows in production environments.
- Collaborate with data scientists, data engineers, and software engineers to streamline ML model development and deployment.
- Develop robust and scalable CI/CD pipelines for continuous model integration, testing, and deployment.
- Manage and optimize distributed data processing pipelines using PySpark.
- Deploy and maintain ML models on cloud platforms (AWS & Azure).
- Use Kubernetes to manage containerized applications and ensure scalability and high availability.
- Monitor model performance, data drift, and system reliability in production.
- Implement model versioning, reproducibility, and governance using tools like MLflow, DVC, or Kubeflow.
- Drive automation and best practices in MLOps across the organization.
Requirements:
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field.
- 7+ years of industry experience with a focus on MLOps, machine learning systems, or data engineering.
- Strong programming experience in Python with knowledge of ML libraries (scikit-learn, pandas, etc.).
- Advanced skills in PySpark for distributed data processing.
- Hands-on experience with both AWS and Azure cloud platforms, including services for ML and data workflows.
- Proficient in Docker and Kubernetes for containerized deployment and orchestration.
- Experience with CI/CD tools (e.g., Jenkins, GitHub Actions, Azure DevOps).
- Deep understanding of software development best practices, Agile methodologies, and DevOps culture.
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