Salih Siddiqi

Built RAG pipelines using vLLM, Typesense with real-time streaming, and PEFT fine-tuning of open-weight models, boosting search performance by 40%. Spearheaded diffusion-based pipelines and advanced TTS to transform natural language prompts into rich multimedia content, leveraging agentic frameworks and vector databases to create autonomous agents.

Built a search engine using transformer-based semantic vectorization in ElasticSearch and deployed a two-tower neural network to boost content relevance by 30%. Developed conversational AI engines using GPT-like models, implementing features like Explain-AI, Exam-AI, and Mind Maps, employing prompt engineering, PEFT, and RAG for personalized learning.

Developed an unsupervised learning system to address user-level cold start challenges, boosting key performance indicators by 10%. Introduced a Transformer-based hybrid recommendation engine for streaming content, increasing personalized suggestions and discovered content by 36%, and achieved 10x speed improvements in collaborative filtering via GPU-accelerated ALS/Matrix Factorization.

Led a team of four engineers to drive end-to-end product development and technical strategy, ensuring solutions aligned with long-term business objectives. Managed the entire product lifecycle from requirements gathering to production deployment, while ensuring technical strategies supported CDS Group’s long-term goals.

Contributed to an award-winning email and audience development solution for top-tier publishers, enhancing targeted campaign delivery and optimizing user engagement through robust architecture and implementation. Developed a comprehensive Android application serving as a digital medical directory, enabling remote diagnosis by efficiently matching patient symptoms with relevant healthcare providers

Worked on the integration of SAP and Microsoft SharePoint. Contributed to streamlining business processes through effective system integration.

Specialized in Cognitive Technical Systems, focusing on Machine Learning, Reinforcement Learning, Computer Vision, and Deep Natural Language Processing. Gained expertise in areas such as Information Retrieval, Robotics, Recommendation Systems, and Distributed Systems.

Completed a Bachelor of Science in Computer Science. The program provided a foundational understanding of computer science principles and practices.