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Senior Data Scientist

Senior Data Scientist

BirdeyeGurugram, Haryana, India
27 days ago
Job description

Organization Snapshot :

Birdeye is the leading all-in-one Experience Marketing platform , trusted by over 100,000+ businesses worldwide to power customer acquisition, engagement, and retention through AI-driven automation and reputation intelligence. From local businesses to global enterprises, Birdeye enables brands to deliver exceptional customer experiences across every digital touchpoint.

As we enter our next phase of global scale and product-led growth , AI is no longer an add-on—it’s at the very heart of our innovation strategy . Our future is being built on Large Language Models (LLMs), Generative AI, Conversational AI, and intelligent automation that can personalize and enhance every customer interaction in real time.

Job Overview :

Birdeye is seeking a Senior Data Scientist – NLP & Generative AI to help reimagine how businesses interact with customers at scale through production-grade, LLM-powered AI systems . If you’re passionate about building autonomous, intelligent, and conversational systems , this role offers the perfect platform to shape the next generation of agentic AI technologies.

As part of our core AI / ML team, you'll design, deploy, and optimize end-to-end intelligent systems —spanning LLM fine-tuning , Conversational AI , Natural Language Understanding (NLU) , Retrieval-Augmented Generation (RAG) , and Autonomous Agent frameworks .

This is a high-impact IC role ideal for technologists who thrive at the intersection of deep NLP research and scalable engineering .

Key Responsibilities :

LLM, GenAI & Agentic AI Systems

  • Architect and deploy LLM-based frameworks using GPT, LLaMA, Claude, Mistral, and open-source models.
  • Implement fine-tuning , LoRA , PEFT , instruction tuning , and prompt tuning strategies for production-grade performance.
  • Build autonomous AI agents with tool use , short / long-term memory , planning , and multi-agent orchestration (using LangChain Agents, Semantic Kernel, Haystack, or custom frameworks).
  • Design RAG pipelines with vector databases ( Pinecone , FAISS , Weaviate ) for domain-specific contextualization.

Conversational AI & NLP Engineering

  • Build Transformer-based Conversational AI systems for dynamic, goal-oriented dialog—leveraging orchestration tools like LangChain, Rasa, and LLMFlow.
  • Implement NLP solutions for semantic search , NER , summarization , intent detection , text classification , and knowledge extraction .
  • Integrate modern NLP toolkits : SpaCy, BERT / RoBERTa, GloVe, Word2Vec, NLTK , and HuggingFace Transformers .
  • Handle multilingual NLP, contextual embeddings, and dialogue state tracking for real-time systems.

    • Scalable AI / ML Engineering

  • Build and serve models using Python , FastAPI , gRPC , and REST APIs .
  • Containerize applications with Docker , deploy using Kubernetes , and orchestrate with CI / CD workflows.
  • Ensure production-grade reliability, latency optimization, observability, and failover mechanisms.

    • Cloud & MLOps Infrastructure

  • Deploy on AWS SageMaker , Azure ML Studio , or Google Vertex AI , integrating with serverless and auto-scaling services.
  • Own end-to-end MLOps pipelines : model training, versioning, monitoring, and retraining using MLflow , Kubeflow , or TFX .

    • Cross-Functional Collaboration

  • Partner with Product, Engineering, and Design teams to define AI-first experiences.
  • Translate ambiguous business problems into structured ML / AI projects with measurable ROI.
  • Contribute to roadmap planning, POCs, technical whitepapers, and architectural reviews.

    • Technical Skillset Required

  • Programming : Expert in Python , with strong OOP and data structure fundamentals.
  • Frameworks : Proficient in PyTorch , TensorFlow , Hugging Face Transformers , LangChain , OpenAI / Anthropic APIs .
  • NLP / LLM : Strong grasp of Transformer architecture , Attention mechanisms , self-supervised learning , and LLM evaluation techniques .
  • MLOps : Skilled in CI / CD tools, FastAPI , Docker , Kubernetes , and deployment automation on AWS / Azure / GCP .
  • Databases : Hands-on with SQL / NoSQL databases, Vector DBs , and retrieval systems.
  • Tooling : Familiarity with Haystack , Rasa , Semantic Kernel , LangChain Agents , and memory-based orchestration for agents.
  • Applied Research : Experience integrating recent GenAI research (AutoGPT-style agents, Toolformer, etc.) into production systems.

    • Bonus Points

  • Contributions to open-source NLP or LLM projects.
  • Publications in AI / NLP / ML conferences or journals.
  • Experience in Online Reputation Management (ORM) , martech, or CX platforms.
  • Familiarity with reinforcement learning , multi-modal AI , or few-shot learning at scale.
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    Senior Data Scientist • Gurugram, Haryana, India