We are looking for an experienced and forward-thinking Data Scientist with 4 to 7 years of expertise to design, build, and scale our next-generation Artificial Intelligence capabilities.

In this role, you will bridge the gap between core Machine Learning and cutting-edge Generative AIspecifically focusing on Large Language Models (LLMs), Advanced RAG pipelines, and Agentic workflows.

If you are passionate about productionizing scalable AI systems, maintaining elite software engineering standards, and driving architectural decisions, we want you on our team.

Role : Data Scientist

Function : Data Science & Machine Learning

Experience : 4 - 7 Years

Location : Bangalore / Gurgaon

Key Responsibilities :

- GenAI Architecture & Deployment : Design, build, and deploy highly scalable, cost-effective LLM architectures, Retrieval-Augmented Generation (RAG) pipelines, and autonomous agent-based systems.

- Production Optimization : Architect and optimize LLM inference and deployment pipelines to ensure low-latency, high-throughput, and cost-efficient production operations.

- Collaboration : Partner closely with data science, core research, and product teams to translate business requirements into rapid prototypes and robust production-ready GenAI solutions.

- Engineering Excellence : Drive software engineering best practices within the AI team, ensuring clean code, rigorous unit testing (TDD), reproducibility, concurrency, and robust CI/CD integration.

- Mentorship : Act as a technical mentor for junior engineers, fostering a culture of continuous learning and technical rigor.

- Governance : Ensure all implementations align with ethical, secure, and responsible AI development guidelines.

Required Technical Skills & Qualifications :

Core Data Science & Deep Learning :

- Advanced proficiency in Python with exceptionally strong fundamentals in NumPy, Pandas, and Scikit-learn.

- Deep learning expertise using PyTorch or TensorFlow frameworks.

Generative AI & Agentic Frameworks :

- Extensive hands-on experience with LLM ecosystems, specifically Hugging Face Transformers and LangChain (covering advanced prompting, evaluation, and fine-tuning).

- Strong, demonstrable experience working with Agentic AI frameworks such as AutoGen, CrewAI, or LangGraph.

- Deep understanding of advanced RAG pipelines, semantic search mechanics, and embedding models.

Software Engineering :

- Solid foundations in modern software development, including microservices architecture, Test-Driven Development (TDD), and concurrency/asynchronous programming.

Good-to-Have Skills (Preferred Qualifications) :

- Model Efficiency : Production-level experience with model optimization techniques including Quantization (GPTQ, AWQ, GGUF), pruning, and distillation.

- Multimodal AI : Exposure to multimodal models across text, vision, and audio frameworks (e., CLIP, BLIP, Whisper, LLaVA).

- LLM Serving & Vector Databases : Experience serving models via FastAPI and orchestrating production vector databases like FAISS, Pinecone, or Chroma.

- Cloud & MLOps Infrastructure : Familiarity with Docker, Kubernetes/Helm, Airflow, and cloud-native AI deployment environments (e., AWS SageMaker, Azure AI, or GCP Vertex AI).

- Experiment Tracking & Data Pipelines : Experience utilizing MLflow and Git for tracking/versioning, along with building ELT/ETL pipelines utilizing data warehouses like Snowflake