Machine Learning Engineer - Data Pipeline
Tasks
- Architect and implement data indexing and search algorithms
- Build and maintain backend services for data storage and synchronization
- Collaborate with research and engineering teams for data flow
- Deploy solutions on Kubernetes and perform system checks
- Design and develop data processing pipelines
- Develop and deploy scalable distributed systems for large data volumes
- Implement machine learning models for data quality and diversity
- Lead data acquisition projects including web crawling
Perks/Benefits
- N/A
Skills/Tech-stack
Algorithm Design | Data Filtering | Data Generation | Data Processing | Data Processing Pipelines | Data extraction | Data indexing | Data labeling | Deep learning | Distributed Systems | Docker | HDFS | Hadoop | Information Retrieval | Infrastructure as Code | Key-Value Databases | Key-value | Kubernetes | Machine Learning | Multiprocessing | Processing pipelines | PyTorch | Python | Ray | Scrapy | Search Systems | Selenium | Synthetic Data Generation | Synthetic data | Web Crawling | “as-code”
Education
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