Arindom Bora

WORK HISTORY

EDUCATION

ABOUT ARINDOM BORA

I’m a Software Engineer (SDE-2) at Lowe’s, working on large-scale search and discovery systems that operate in near real-time and directly influence user experience and business outcomes. My work spans semantic search, query autocomplete, and item ranking—focusing on building low-latency, high-relevance systems powered by machine learning and distributed data processing.I’ve led and contributed to end-to-end development of semantic search capabilities by integrating vector databases (Weaviate) into production pipelines, along with designing scalable data pipelines in PySpark for indexing, embeddings, and retrieval. I’ve also implemented personalization using Learning-to-Rank models (LightGBM) across autocomplete and ranking systems, improving engagement and contributing to ~$73M in annual revenue uplift. A strong emphasis in my work is on performance engineering—achieving sub-30ms P95 latencies while reducing infrastructure costs.My technical toolkit includes Python, Java, and C++, along with frameworks and systems like FastAPI, Spring Boot, Apache Spark, Airflow, and various distributed databases (MongoDB, Cassandra, Redis, PostgreSQL). I enjoy working at the intersection of backend systems, machine learning, and search relevance.Beyond work, I have a strong foundation in mathematics and machine learning, built through rigorous self-study of linear algebra, probability, and statistical learning. I’m also an active competitive programmer (Top 4% on LeetCode, problems solved), which sharpens my problem-solving and algorithmic thinking.I’m particularly interested in building intelligent, scalable systems and solving challenging problems in search, ranking, and applied machine learning.