Recommendation Systems Engineering, Semantic Content Search, applying GenAI/LLM and focusing on candidate and ML feature generation, serving platform. Streaming system and Machine Learning Platform (ML Platform)

• Building and evolving large-scale data processing systems which score tens of billions of events a day with minimal latency, as well as ingesting, storing and accessing >10TB of ML features and metadata across offline, nearline and online paradigms

• Working with product teams across all lines of business to build platforms that onboard new use-cases quickly and enable product engineers to experiment with new ideas with minimal friction.

• Collaborating with AI teams across the company to build infrastructure to enable quick experimentation with tens of ML models per quarter using thousands of features

• Working closely with our data/AI Infra partners to build novel solutions for our ever-growing scaling needs

Applying GenAI/LLM technologies for search and recommendation, Sequence feature generation for LLM, transact embedding and MTL, training and inference.

Kafka, Flink, Samza (Streaming near real-time insights for machine learning use-cases), Apache Beam, Graph Database (Fanout), NoSql (Cassandra) for ML Features), KV Store - RocksDB, Couchbase(Online Features), Spark, Hadoop, HDFS, Hive(Offline Batch), Data lake (Iceberg), SQL - TiDB (Document DB, metadata), Trino, Pinot (Analytics DB, aggregation), Event-Driven ChangeCapture Streaming, Airflow, Flyte and Azkaban workflow orchestrator.

Event and Streaming Platform:

• Drive and work on algorithm and architecture design, execute and deliver fault-tolerant Kafka systems.

• Build and support Kafka over multi-region architecture on both on-premise and in the cloud to provide high availability and strong consistency.

• Design and Building stream processing solutions like Kafka Streams and KSQL to perform rich, real-time, transformation and querying of data in Kafka

• Design and deliver data pipelines built through Kafka Connect.

• Integrate Elastic search with Kafka using Metricbeat, Filebeat, and logstash for monitor-ing and reprocessing.

• Responsible for development and maintenance of CPM (Continuous Performance Management) HXM – Human Experience Management – HR System

• Monolithic to microservice, design and implement using Event-Driven Architecture.

• Design and deliver Event-Driven Architecture using Apache Kafka and KSQL

· Complete life cycle of the project including analyzing the requirements, designing, developing and testing.

· Development of REST-based services LinkedIn integration, resume parser, and backend data services for Offer Approval Management System.

· Design and deliver Offer approval management using Even driven architecture using Kafka.

· Solely responsible for maintaining a “Candidate Experience Application” backend Rest services. Which is used by candidates to search (Elastic search) and apply for Jobs and application.

· Designed developed and tested applications and components using Spring, Oracle DB, and Cassandra.

Developed and maintained scalable Order management application used by Herbalife customer for shopping Herbalife products online.

Application development using JSF and this is a mission-critical application can never get down.

Development of REST based services.

Implement a test case using JUnit.

Designed, developed and tested applications/components

Performed peer code reviews, completed documentation