Key Responsibilities:
- Develop and maintain machine learning models and pipelines using Python.
- Collaborate with data scientists to implement algorithms and optimize model performance.
- Containerize ML applications using Docker and orchestrate deployments with Kubernetes.
- Monitor, scale, and troubleshoot machine learning services in production environments.
- Write clean, reusable, and well-documented code following best practices.
- Automate workflows and CI/CD pipelines for ML models and applications.
- Participate in code reviews and ensure adherence to security and quality standards.
Key Skills Required:
- Strong proficiency in Python programming
- Hands-on experience with Machine Learning frameworks such as TensorFlow, PyTorch, or scikit-learn
- Familiarity with Kubernetes for container orchestration and deployment
- Experience with Docker and containerization best practices
- Knowledge of data preprocessing, feature engineering, and model evaluation
- Experience with cloud platforms (AWS, GCP, Azure) is a plus
- Understanding of CI/CD pipelines and DevOps practices
- Good problem-solving, communication, and collaboration skills
Skills Required
Machine Learning, Python, Docker, Kubernetes, Aws, Gcp, Azure