Senior Associate Data Science L2

Epsilon
Posted on
Epsilon logo

Experience
5 - 8 yrs
Job Location
Bengaluru, India
Vacancy
1
Designation
Senior Data Scientist Associate
Job Type
ONSITE

Job Description

Overview Senior Associate L2 Data Science (Generative AI) Publicis Sapient is looking for a Senior Associate L2 Data Science (Generative AI) to join our Data & AI team and drive next-generation AI-powered solutions.

In this role, you will design and implement scalable GenAI systems leveraging Large Language Models (LLMs) and advanced AI techniques to solve complex business problems. You will work at the forefront of innovation, building intelligent systems that deliver personalized, data-driven digital experiences and unlock business value for global clients.

Your Impact:

  • Design and implement AI-driven systems that transform user experiences and business processes.
  • Fine-tune and adapt large language models (LLMs) for domain-specific applications using advanced techniques like RLHF and instruction tuning.
  • Build intelligent AI agents to solve complex business challenges using generative AI technologies.
  • Develop and optimize NLP pipelines for search relevance, intent detection, and content generation.
  • Integrate multi-modal systems (text, images, metadata) to enhance user insights and interactions.
  • Optimize AI pipelines for scalability, performance, and real-time responsiveness in production.
  • Deploy and scale GenAI solutions on cloud platforms such as AWS, Azure, or GCP.

Qualifications

  • 5.5 8 years of experience with at least 2 years in Generative AI.
  • Strong experience fine-tuning and deploying large language models (LLMs, VLLMs, vision models).
  • Hands-on experience with GenAI frameworks like LangChain and LlamaIndex.
  • Experience with vector databases such as Milvus, FAISS, or ChromaDB.
  • Knowledge of distributed training/inference frameworks like Ray, vLLM, or BentoML.
  • Experience working with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).
  • Strong understanding of prompt engineering, ML workflows and Agentic AI.

Additional information

  • Experience building AI agents using frameworks like LangGraph, CrewAI, or Autogen.
  • Knowledge of open-source LLM ecosystems (HuggingFace models).
  • Experience in deploying production-ready GenAI solutions using OpenShift or Kubernetes.
  • Strong understanding of multi-modal AI models (LLM, VLM, GANs, VAEs).
  • Exposure to DevOps practices for scalable AI systems.
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