PubMatic hiring Software Engineer, AI-Powered Advertising Agents
Company: PubMatic
Location: Pune, India
Experience: Experienced
Qualification: BE/BTech in CS/IT or equivalent
About the Role
Join PubMatic’s cutting-edge AI team to revolutionize programmatic advertising using the power of Generative AI and AI agents. This role focuses on developing advanced, production-ready AI solutions using LLMs, Retrieval-Augmented Generation (RAG), vector databases, and other frontier technologies. You’ll be at the core of crafting intelligent, adaptive systems to enhance automation and contextual intelligence across PubMatic’s ad tech platform.
Key Responsibilities
Collaborate with cross-functional teams to develop innovative AI-driven advertising agents
Fine-tune and deploy large language models (LLMs) for domain-specific use cases
Build and optimize RAG-based agents, integrating real-time and external data sources
Design and manage vector databases (e.g., FAISS, Pinecone, Weaviate) for scalable information retrieval
Engineer advanced prompting strategies for precise, contextual LLM responses
Implement evaluation frameworks (e.g., Evals) for assessing model quality
Work on end-to-end AI model lifecycle: from experimentation to integration into products
Stay updated with AI advancements and apply them to drive real product innovation
Monitor and optimize model performance for efficiency and scalability
Must-Have Skills
Solid knowledge of LLMs (GPT, BERT, T5, etc.) and transformer architecture
Hands-on experience building RAG systems and context-aware AI agents
Proficiency in vector databases and indexing algorithms
Strong programming in Python, with experience in PyTorch, TensorFlow, and Hugging Face Transformers
Skilled in prompt engineering and performance optimization of generative models
Experience handling large datasets and vectorization techniques
Excellent communication and stakeholder presentation skills
Nice-to-Have
Experience with graph neural networks (GNNs) and knowledge graph embeddings
Exposure to cloud platforms (AWS, GCP, Azure), Docker, and Kubernetes
Ability to train small base models on domain-specific data
Published work or contributions in AI/LLM research fields
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