Description

You will design and deploy scalable machine learning solutions in production environments.

Responsibilities

• Deploy scalable ML solutions into production environments.
• Build and maintain data pipelines and ETL processes.
• Manage big data processing using distributed computing.
• Implement data lake management using Apache Iceberg.
• Troubleshoot performance issues within machine learning workflows.

Required Skills

• 5+ years of experience in Machine Learning Engineering or a related role.
• Proficiency in Python and SQL.
• Hands-on experience with JAX for numerical computing.
• Advanced knowledge of Apache Spark for big data processing.
• Experience with ML frameworks including TensorFlow and PyTorch.
• Hands-on experience with Apache Iceberg for data lake management.
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Strong understanding of ETL processes and distributed computing.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.

Preferred Skills

• Familiarity with MLOps practices and tools like MLflow or Kubeflow.
• Experience with containerization and orchestration using Docker and Kubernetes.
• Knowledge of data versioning and governance using Iceberg.

Key Skills

Education

Bachelor's or Master's degrees