Job Title

About the RoleWe are seeking a hands-onAI/ML Engineerwith deep expertise inRetrieval-Augmented Generation (RAG) agents ,Small Language Model (SLM) fine-tuning , andcustom dataset workflows . You'll work closely with our AI research and product teams to build production-grade models, deploy APIs, and enable next-gen AI-powered experiences. Key ResponsibilitiesDesign and build RAG-based solutions using vector databases and semantic search. Fine-tune open-source SLMs (e.g., Mistral, LLaMA, Phi, etc.) on custom datasets. Develop robust training and evaluation pipelines with reproducibility. Create and expose REST APIs for model inference usingFastAPI . Build lightweight frontends or internal demos withStreamlitfor rapid validation. Analyze model performance and iterate quickly on experiments. Document processes and contribute to knowledge-sharing within the team. Must-Have Skills3–5 years of experience in applied ML/AI engineering roles. Expert in Python and common AI frameworks (Transformers, PyTorch/TensorFlow). Deep understanding of RAG architecture, vector stores (FAISS, Pinecone, Weaviate). Experience with fine-tuning transformer models and instruction-tuned SLMs. Proficient with FastAPI for backend API deployment and Streamlit for prototyping. Knowledge of tokenization, embeddings, training loops, and evaluation metrics. Nice to HaveFamiliarity with LangChain, Hugging Face ecosystem, and OpenAI APIs. Experience with Docker, GitHub Actions, and cloud model deployment (AWS/GCP/Azure). Exposure to experiment tracking tools like MLFlow, Weights & Biases. What We OfferBuild core tech for next-gen AI products with real-world impact. Autonomy and ownership in shaping AI components from research to production. Competitive salary, flexible remote work policy, and a growth-driven environment.