Bengaluru, Karnataka, India
- I'm Kuldeep Singh Sidhu, with 8+ years of experience in deploying data science solutions at scale, specializing in machine learning/ deep learning (TensorFlow, PyTorch) and data science (Python). - I have published open-source packages that have garnered 500,000+ downloads collectively. - I frequently answer data science questions on open platforms across the web, currently ranked top 5% on StackOverflow - Passionate about AI (Neural Networks, GANs) and big data analytics (Spark). - Expert in deep learning (CNNs, RNNs) and natural language processing (BERT, GPT, LLama, Mixtral, LangChain). - Skilled in developing AI-driven systems (Keras, Scikit-learn) for business outcomes. - Committed to continuous learning and effective teamwork - Expertise in TensorFlow, PySpark, Elasticsearch, SQL, R, Java, Docker, Kubernetes, and cloud technologies (GCP, AWS, Azure).
Responsible for improving Walmart Search by understanding the queries made by 300M+ monthly active customers to surface and recommend the most relevant products from a catalog of 1B+, directly impacting Walmart's half-trillion-dollar annual revenue. • Built a multi-agent system for fine-grained relevance using LangGraph, driving one of the largest GMV uplifts at $300M+ • Designed a multi-layered retrieval system that narrows the funnel from billions of products down to the few hundred shown to each customer, leveraging learning-to-rank (LTR) and modern retrieval frameworks • Developed token-weighting models to better capture the importance of individual query and item tokens, improving retrieval quality • Unified multiple models into a single architecture, streamlining feature engineering and accelerating iteration time, contributing $10M+ in GMV impact Skills: Recommendation Systems, Information Retrieval, Learning to Rank, Large Language Models, Natural Language Processing, Deep Learning, Multi-Agent Systems, System Design Technologies: LangGraph, LangChain, Python, Transformers, BERT, Elasticsearch, PySpark, ONNX, FastAPI, GCP, Vertex AI
Was responsible for improving Lowe’s search experience by understanding 3 billion+ search queries made by our Lowe’s customers on the digital platforms to personalize/recommend 5 million+ products and impact our ∼100 Billion USD revenue annually. Collaborating across teams to deliver high-performance and low-latency models • Created a Query Classification model for multi-class classification using TensorFlow, PySpark, TensorFlow Serving(TFX) & FastAPI with low latency throughput for search ranking. • Finetuned LLM for Retrieval Augmented Generation (RAG) based on user search query using LangChain with low-latency serving using vLLM and DeepSpeed-MII • Trained a domain-specific BERT to have an accurate & efficient representation of queries and documents related to the home-improvement domain on over 20 million open-source (Semantic Web 2020, Amazon 2018, etc) & in-house data points. The language model outperforms distilled BERT with 20% fewer parameters improving latency. • Conceptualised and built a behavioural tagging model that maps attributes between products and user queries for the top business-driving queries by mining relationships over millions of data points using PySpark. • Expanded search query autocomplete candidate list by 90%+, resulting in more contextual, seasonal and personalised autocomplete suggestions. • Worked on enriching our Elastic Index with user behaviour signals resulting in 16% better recall • Created a 1000 times faster lexical matcher based on SymSpell to compute the importance of each token in a user query for over 3 million + unigrams and bigrams • Created a real-time low latency Spanish Translation model for non-English search queries Skills: Recommendation Systems, Natural Language Processing, Information retrieval, Deep Learning, System design Technologies: Tensorflow, PyTorch, Transformers, BERT, Elasticsearch, PySpark, ONNX, FastAPI, GCP, VertexAI
Worked on implementing new features for the JustDial app with 100+ million downloads. Built the very first JD Social (app homepage) content ingestion and recommendation system. • Created a ChatBot with functionalities to serve the user on all 72 verticals (Chatting, Flights, Restaurants, General Search, etc.) that JustDial works on using RASA, SPACY, ChatterBot, Tensorflow, DBPedia • Built a recommendation system for JD Social (JustDial social network) using collaborative filtering and item-based filtering • Created content-based monetizable suggestions. (Eg. suggestion to book tickets to a destination covered in a travel article or buy a product discussed in the article) using BERT (Transfer Learning) with f1 score of 0.88 • Summarising news articles using sequence rank to reduce content consumption time. • Researched ways to do Natural Language Processing on Indian Languages Skills: Natural Language Processing(NLP), ChatBot, Data Structures, System design Technologies: Tensorflow, scikit-learn, RASA, BERT, Pandas, NumPy, Flask
Automating processes using Python libraries such as Pandas, OpenPyXl, Keras, etc. and Automation Anywhere
Software development for Power Curve generation using:JSP, Java,Bootstrap and MySQL by performing data analysis on Sensor data