Posted:1 day ago|
Platform:
On-site
Full Time
3. Design, build, and maintain scalable infrastructure for high-performance indexing, search engines, and vector databases (e.g., Pinecone, Weaviate, FAISS).
4. Implement and optimize large-scale ETL pipelines, ensuring efficient data ingestion, transformation, and indexing workflows.
5. Lead the development of end-to-end indexing pipelines, from data ingestion to API delivery, supporting millions of data points.
6. Deploy and manage containerized services (Docker, Kubernetes) on cloud platforms (AWS, Azure, GCP) via infrastructure-as-code (e.g., Terraform, Pulumi).
7. Collaborate on building and enhancing user-facing APIs that provide developers with advanced data retrieval capabilities.
8. Focus on creating high-performance systems that scale effortlessly, ensuring optimal performance in production environments with massive datasets.
9. Stay updated on the latest advancements in LLMs, indexing techniques, and cloud technologies to integrate them into cutting-edge applications.
10. Drive ML and AI best practices across the organization to ensure scalable, maintainable, and secure AI infrastructure.
Bachelor's or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field. PhD preferred.
Certifications in Cloud Computing (AWS, Azure, GCP) and ML technologies are a plus.
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