Imran S.

I am a seasoned Machine Learning and Data Engineer with a proven track record of designing and developing cutting-edge solutions for OTT platforms. My expertise lies at the intersection of data engineering, machine learning, and scalable system architecture, enabling personalized user experiences and streamlined workflows. What I Do: Recommendation Engines: Architect and develop intelligent, scalable recommendation systems that enhance content discovery and engagement. MLOps Pipelines: Build robust MLOps workflows to automate model deployment, monitoring, and scaling, ensuring seamless integration into production. Data Pipelines: Design and implement efficient ETL processes using PySpark and Delta Lake, optimizing data storage, processing, and transformation. Python Development: Leverage Python for crafting scalable, maintainable, and efficient code tailored to data-centric applications. Core Strengths: Expertise in Delta Lake for managing large-scale structured and unstructured datasets. Proficient in PySpark, delivering high-performance distributed data processing. Strong foundation in building architectures that support scalability and high availability. Deep understanding of recommendation systems and their role in enhancing OTT user experiences. Passion for Innovation: I am driven by my passion for leveraging data to solve real-world problems. Whether it's optimizing a recommendation algorithm, automating a machine learning workflow, or architecting a data lake for efficiency and scalability, I thrive on building systems that make a measurable impact. On a Mission: To build robust, future-ready solutions that empower businesses to make data-driven decisions and deliver exceptional user experiences. - NLP with LLMs - VQA with VLMs - STT, TTS, transcription with speech models (Whisper LLM) - HuggingFace transformer library - Vector databases - Agents - Graph RAG - Embedding models - Recommendation Systems