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Builds and optimizes search systems that power both AI agents and human users, focusing on hybrid retrieval, ranking models, and relevance metrics using Lucene/Elasticsearch and embeddings.
Leads the development of AI-powered search ranking and relevance systems for Databricks' platform, focusing on ML models, NLP pipelines, and evaluation frameworks to improve asset discovery at scale.
Senior engineer building and optimizing Databricks' Delta Lake backend systems to handle massive-scale data writes with high performance and reliability.
Lead the design and development of Databricks' next-generation Materialized Views system, optimizing query performance and ETL workloads at massive scale using distributed systems and database technologies.
Design and lead Databricks' next-generation multi-cloud networking infrastructure, scaling connectivity and observability for millions of VMs while shaping core platform architecture.
Builds and scales evaluation infrastructure for AI agents at a data/AI platform company, designing systems that measure and improve agent quality across research and production.
Designs and runs the infrastructure that powers AI research at Databricks, building systems to schedule and orchestrate large-scale training and inference workloads across thousands of GPUs.
Designs and scales backend infrastructure for a data/AI platform, working on distributed systems, cloud storage, and Kubernetes-based services in Bengaluru.
Builds and maintains Databricks' billing, cost optimization, and resource governance systems, ensuring accurate usage tracking and commercialization for enterprise customers using cloud-native infrastructure.
Designs and builds autonomous data systems for Databricks' Managed Tables, optimizing storage and performance at massive scale using distributed systems and AI-driven tools.
Designs and builds distributed data storage and processing systems for Databricks' big data platform, focusing on Apache Spark, Delta Lake, and cloud storage backends like AWS S3 and Azure Blob Store.
Designs and builds Databricks' billing, pricing, and cost-optimization systems, ensuring accurate usage tracking and seamless customer billing across AWS, GCP, and Azure.
Build and lead the Spark Structured Streaming engine, designing state-of-the-art stream processing features and improving latency, throughput, and cost for Databricks’ data and AI platform.
Designs and builds next-generation database engine internals for Databricks' Lakehouse platform, focusing on query optimization, distributed execution, and storage systems to outperform traditional data warehouses.
Builds and optimizes distributed data storage and processing systems for Databricks' big data and AI platform, working on projects like Apache Spark, Delta Lake, and performance engineering.
A senior engineer leads the architecture and development of user onboarding and activation flows for a cloud-based data platform, guiding a team to improve customer adoption and growth.
Build and evolve Databricks’ core authorization service, migrating permission checks to a unified model and adding fine-grained access controls for users, apps, and workloads.
Design and build AI-powered systems to help Databricks customers resolve technical issues faster using LLMs and retrieval systems, operating at the intersection of product development and machine learning.
Leads the technical vision for Databricks' search ranking, relevance, and evaluation systems, blending keyword, vector, and hybrid retrieval to improve enterprise AI applications.
Build and scale AI voice agents handling millions of real-time customer calls for major brands, using Python, AWS, and Twilio to orchestrate complex workflows and low-latency inference.
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