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PubMatic , Pune is hiring !!

  Pubmatic      Pune      0 - 20 Years
Backend
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Job Description

PubMatic , Pune is hiring !! Skip the resume, Beat the assessment  !!!
We're building AI agents that power advertising at global scale — RAG, LLMs, vector search, multi-agent orchestration. Real production. Real impact.

Here's the twist
Open assessment for everyone who fits the JD. No gatekeeping, no "who you know." Top rankers get fast-tracked straight to interviews.

Don't apply. Prove it in Next 7 days

???? Assessment(90 Min) : https://lnkd.in/dda82src

JD: https://lnkd.in/d92Cxnim
 
What You'll Do:
  • Lead the design, development, and deployment of AI-driven features. Drive end-to-end ownership—from feasibility analysis and design specifications to execution and release—while ensuring quick iterations based on customer feedback in a fast-paced Agile environment. 
  • Spearhead technical design meetings and produce detailed design documents that outline scalable, secure, and robust AI architectures. 
  • Ensure that the solutions are aligned with long-term product strategy and technical roadmaps. 
  • Implement and optimize LLMs for specific use cases, including fine-tuning models, deploying pre-trained models, and evaluating their performance. 
  • Develop AI agents powered by RAG systems, integrating external knowledge sources to improve the accuracy and relevance of generated content. 
  • Design, implement, and optimize vector databases (e.g., FAISS, Pinecone, Weaviate) for efficient and scalable vector search, and work on various vector indexing algorithms. 
  • Create sophisticated prompts and fine-tune them to improve the performance of LLMs in generating precise and contextually relevant responses. 
  • Utilize evaluation frameworks and metrics (e.g., Evals) to assess and improve the performance of generative models and AI systems. 
  • Work with data scientists, engineers, and product teams to integrate AI-driven capabilities into customer-facing products and internal tools. 
  • Stay up to date with the latest research and trends in LLMs, RAG, and generative AI technologies to drive innovation in the company’s offerings. 
  • Continuously monitor and optimize models to improve their performance, scalability, and cost efficiency.

We'd Love for You to Have:
  • 2 to 10 years of experience and strong understanding of LLMs and their underlying principles — transformer architecture, attention mechanisms, and hyperparameter tuning.
  • Proven experience designing and building AI agents, including multi-agent orchestration, tool-use patterns, multi-step planning, and agent memory architectures (short-term and long-term).
  • Hands-on experience with agentic frameworks such as LangGraph, CrewAI, or AutoGen, and familiarity with RAG pipelines that integrate external knowledge sources (documents, databases, APIs).
  • In-depth knowledge of vector databases and indexing algorithms; practical experience with FAISS, Pinecone, Weaviate, or Milvus.
  • Experience with agent observability, tracing, and guardrails — tools like Langfuse or equivalent — to ensure reliability, safety, and debuggability of agentic systems.
  • Proficiency in prompt engineering — crafting, iterating, and optimizing complex prompts for context-sensitive, domain-specific LLM outputs.
  • Familiarity with Evals and other performance evaluation tools for measuring model quality, relevance, and efficiency. 
  • Proficiency in Python and experience with machine learning libraries such as TensorFlow, PyTorch, and Hugging Face Transformers. 
  • Experience with data preprocessing, vectorization, and handling large-scale datasets. 
  • Ability to present complex technical ideas and results to both technical and non-technical stakeholders. 

Nice-to-Have:
  • Experience in building AI agents using graph-based architectures, including knowledge graph embeddings and graph neural networks (GNNs). 
  • Experience with training small base models using custom data, including data collection, pre-processing, and fine-tuning models to specific domains or tasks. 
  • Familiarity with deploying AI models on cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). 
  • Familiarity with programmatic advertising, RTB, or ad auction mechanics.
  • Knowledge of MCP (Model Context Protocol) or similar tool-integration standards
  • Publication or contributions to research in AI, LLMs, or related fields.

Qualification:
Should have a bachelor’s degree in engineering or an equivalent degree from a well-known institute/university.   
 
Apply from
https://pubmatic.com/job/?gh_jid=5369682008                                                                                               
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