Hire Shailesh - Vector Database Engineer

* Serve as a trusted senior technical advisor for customers developing GenAI solutions, such as Agentic workflows, RAG architectures, querying structured data with natural language, content generation etc. * Architect production-level GenAI & ML workloads for customers using Databricks unified platform, including end-to-end GenAI workflows/ML pipelines, model training/inference optimizations, fine-tuning, evaluation, monitoring, and integration with cloud-native services. * Implement GenAI PoCs for customers, increasing success rates of taking Gen AI use cases and reducing time-to-market. * Collaborate with product, engineering, and research teams to define priorities and influence the product roadmap. * Participate in the larger AI/ML SME community in Databricks, contributing to mentorship and knowledge sharing

* Clients included: Nike, Atlassian, AXA Insurance, Krista Software, Point72 * Areas of expertise: Large Langauge Models(LLMs), Generative AI, Foundation Models, HuggingFace Transformers, LLMOps, Finetuning, Prompt Engineering, Embeddings, Vector Databases (Milvus, Weaviate, Matching Engine Pinecone), RLHF, LangChain * Design, develop, and implement Generative AI & NLP strategy for clients. * Lead efforts to solve business problems using Natural Language Processing, Large Language Models, and Generative AI. Lead technical projects and mentor ML Engineers and Data Scientists. * Build services to expose LLMs from various providers to internal users. (Azure Open AI, Vertex AI, Amazon Bedrock, HuggingFace) * Finetune open source LLMs available for commercial use using the company’s internal datasets – Llama-2, Falcon, MPT, GPT-J, Flan-T5-XXL (Huggingface, Sagemaker, Jumpstart, QLoRA) * Build solutions for Question-Answering and Summarizing on financial documents using Retrieval Augmented Generation (RAG) approach. (LangChain, LlamaIndex, Weaviate, GPT-3.5/4, Claude, FastAPI) * Build Agents to link LLMs with various tools/APIs– Google/Bing Search Agent, CSV agent, SQL Agent, Code interpreter. * Work on Search and Recommendation for grocery items with a Retrieve-Filter-Rank-Reorder approach using customer shopping history and product embeddings. * Utilize various Vector Databases for building Semantic Search solutions - Milvus, Weaviate, Pinceone, Matching Engine * Use Prompt Engineering and functions calling to generate and tailor summaries and insights from financial documents in formats and styles preferred by financial analysts * Develop Named Entity Recognition (NER) service for labeling and extracting 10 kinds of entities from insurance documents. * Work on end-to-end system development including training data generation, building and fine-tuning models, performance evaluation, experiment tracking, model deployment, and iterative improvement

* Lead Machine Learning Engineer responsible for designing and implementing Machine Learning workflows, and productionizing Machine Learning Models * Productionized company’s first Machine Learning Model to serve real time requests with low latency. * Develop and maintain full ownership of the low latency Hotel Sort Service responsible for scoring and ranking list of hotels for real time search requests made by customers on Priceline Website. * Apply personalization and recommendations using customer history for more relevant results * Hotel Image Categorization using Deep learning * Design, build and productionize the machine learning service for finding best “k” flights for a real time search request * Apply Machine Learning techniques for Fraud Detection * Use Apache Spark for large scale data transformation required for analytics and model training * Build proof of concept for architecting an end to end Machine Learning system on Google Cloud Platform * Experiment with Google Vision API for hotel images and Google Cloud Natural Language API for hotel reviews * Design and conduct A/B tests for Data Science experiments * Use Splunk to monitor logs and create alerts * Apply best practices in Java and Python to make code more efficient, scalable, modular and maintainable * Train and mentor new hires and other engineers who joined the team * A high impact role involving work with Data Scientists, Software Engineers and Product Managers. * Attend conferences and trainings: Spark Summit (2017), H2O World (2018), Google Cloud Platform Big Data & Machine Learning Fundamentals Training (2019)