Machine Learning Engineer

Job Description:

Key Qualifications/Responsibilities:

- Manage the entire lifecycle of ML models, from development to deployment and maintenance.

- Develop ML models in Python, using object-oriented programming in a modular manner.

- Utilize AWS SageMaker for building, deploying, and managing ML pipelines.

- Handle model versioning and lifecycle management using DVC and Git.

- Implement scalable and modular solutions with Docker and serverless architectures (e.g., AWS Lambda).

- Design and implement event-driven architectures, including triggers and event sources, to automate and streamline ML workflows.

- Create and manage feature stores to enhance model reuse and efficiency.

- Design and maintain CI/CD pipelines for robust ML model deployment.

- Evaluate model performance using relevant metrics and fine-tune for optimal results.

- Experienced on Data Science models, statistics

Preferred Qualifications:

- Experience with Monorepos

- Experience with large language models (LLMs) and advanced deep learning techniques.

- Knowledge of additional cloud platforms and tools (e.g., Azure, Google Cloud).