Role overview
- Ensuring the building, training, and deployment of machine learning models using AWS SageMaker’s managed infrastructure and automation capabilities to develop scalable and efficient ML solutions.
- Using Amazon Redshift and Amazon S3 for data storage, processing, and analysis required for ML model development and operations.
- Applying Apache Spark and Apache Airflow for large‑scale data processing and pipeline orchestration, ensuring high performance and reliability.
- Managing and optimizing machine learning workloads within Amazon EMR environments, while meeting performance and availability requirements.
- Leveraging Python and key data science libraries (e.g., NumPy, Pandas, Scikit‑learn) for data manipulation, preprocessing, modeling, and analysis.
- Collaborating with data engineering teams to ensure seamless and efficient integration of ML models into production environments.
- Implementing and adhering to best practices for model versioning, monitoring, and CI/CD processes to maintain ML models in optimal condition throughout their lifecycle.
What we're looking for
*Additional Information
Benefits:**
- Full access to foreign language learning platform
- Personalized access to tech learning platforms
- Tailored workshops and trainings to sustain your growth
- Medical subscription
- Meal tickets
- Monthly budget to allocate on flexible benefit platform
- Access to 7 Card services
- Wellbeing activities and gatherings
Tags & focus areas
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