Atul Singh
Staff, Data Scientist | AI CoE @ Warner Bros. Discovery | GenAI, LLMs, AI Agents, MLOps & Scalable ML Platforms
- Role
- Staff, Data Scientist at Warner Bros. Discovery
- Location
- Hyderabad, TG, IN
- LinkedIn followers
- 500 followers
About Atul Singh
Staff, Data Scientist at Warner Bros. Discovery (AI Center of Excellence) building scalable, production-grade AI and ML systems across enterprise and product environments. Specialized in designing end-to-end machine learning platforms covering data ingestion, feature engineering, model training, deployment, monitoring, and optimization.Strong expertise in Machine Learning, Deep Learning, NLP, Generative AI, LLM fine-tuning, and AI agents, with hands-on experience delivering RAG pipelines, intelligent automation, and real-time inference systems. Proven ability to design cloud-native ML architectures leveraging AWS, Azure, and Snowflake, ensuring scalability, reliability, and cost efficiency.Experienced in ML system design, MLOps, and platform engineering, enabling repeatable experimentation, model governance, and lifecycle management. I work closely with product, engineering, and leadership teams to translate ambiguous business problems into robust, scalable AI solutions.Currently focused on building AI platforms and foundational systems that accelerate experimentation, standardize ML workflows, and enable long-term organizational scalability. Passionate about driving technical excellence, mentoring teams, and shaping the future of AI-driven products. Key Expertise:AI & ML Systems • GenAI & LLMs • AI Agents • RAG Architectures • MLOps • Cloud AI (AWS, Azure, Snowflake) • Data Platforms • Scalable System Design
Experience
Staff, Data Scientist
Aug 2025 — Present · Hyderabad, IN
Architecting and scaling enterprise-grade AI and ML platforms supporting data-driven media and digital products.•Designing end-to-end ML systems including ingestion, feature engineering, training, inference, and monitoring pipelines.•Building GenAI-powered applications leveraging LLMs, RAG pipelines, and AI agents for intelligent automation and content intelligence.•Driving architectural decisions across AWS, Azure, and Snowflake with focus on scalability, reliability, and cost efficiency.•Collaborating with product, engineering, and data teams to translate complex business requirements into scalable AI solutions.•Mentoring senior engineers and data scientists; contributing to long-term AI platform strategy and technical standards.
Education
Rajiv Gandhi Prodyogiki Vishwavidyalaya
Bachelor’s Degree
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