Magellanic Cloud - Machine Learning Engineer - R/Python

Job Description :

Key Responsibilities :

- Perform data preprocessing, cleansing, transformation, and feature engineering on both structured and unstructured data.

- Train, evaluate, and optimize ML models for performance, scalability, and accuracy.

- Integrate ML models into production systems and ensure their continuous performance using MLOps practices.

- Leverage cloud platforms, especially Google Cloud Platform (GCP), for scalable model training and deployment (e.g., Vertex AI, BigQuery, Dataflow).

- Develop REST APIs for ML models using Docker and orchestrate deployments via Kubernetes.

- Collaborate closely with data engineers, product managers, and software developers to translate business requirements into technical solutions.

- Monitor and maintain models in production, ensuring stability, performance, and regular updates.

- Maintain best practices in version control, documentation, and continuous integration using Git, GitHub, or GitLab.

Required Qualifications & Skills :

- Proficiency in Python (preferred) or R, along with common machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).

- Solid knowledge of machine learning algorithms including regression, classification, clustering, and deep learning.

- Experience with Natural Language Processing (NLP), Computer Vision, or other advanced AI techniques is a

strong plus.

- Strong expertise in SQL and NoSQL databases, with a deep understanding of data warehousing concepts.

- Demonstrated ability in data blending and transformation, working with structured and unstructured data formats.

- Hands-on experience with GCP tools like Vertex AI, BigQuery, and Dataflow is highly desirable.

- Familiarity with MLOps practices, including model versioning, monitoring, and CI/CD pipelines.

- Working knowledge of Docker and Kubernetes for containerized deployments.

- Proficiency with Git-based version control systems for collaborative development workflows.

Nice to Have :

- Experience working in agile and fast-paced environments.

- Prior experience deploying AI solutions in industries like finance, healthcare, retail, or supply chain.