Senior Python AI Developer

Job Description

?? We?re Hiring: Senior Python Developer (AI/ML) ? 3 to 5 Years Experience Are you passionate about building cutting-edge AI products? Do you enjoy experimenting with LLMs, building scalable RAG systems, and deploying real-world ML solutions? ?? Role: Python Developer ? AI/ML Experience: 3 - 5 years Location: Turbhe, Navi Mumbai (On site) Budget - 5lpa - 12lpa Industry: AI | ML | LLMs | RAG Systems | Cloud ?? What You?ll Work On You will join our AI/ML engineering team and contribute to building production-grade LLM solutions. Your responsibilities include: Developing & optimizing ML models using PyTorch / TensorFlow / Keras Building end-to-end LLM + RAG pipelines using LangChain / LangGraph Working with OpenAI, Anthropic Claude, Azure APIs Fine-tuning models using Hugging Face Transformers Implementing semantic search with embedding models + pgvector Working on transformer-based architectures (BERT, GPT, LLaMA, Mistral) Implementing evaluation & monitoring: RAGAS, LangSmith Developing FastAPI microservices (REST/GraphQL + WebSockets) Integrating vector DBs: pgvector, Pinecone, Weaviate, FAISS, Milvus Deploying using Docker + Kubernetes (EKS/GKE/AKS) Utilizing AWS services: EC2, S3, RDS, SageMaker, Lambda, CloudWatch Managing ML experiments: MLflow / Weights & Biases / Neptune Ensuring secure, robust LLM deployments Contributing to code reviews, AI knowledge sessions & Agile rituals ?? What We?re Looking For 2?5 years Python experience Hands-on with LangChain / LangGraph Strong ML/DL background FastAPI expertise Experience with pgvector & vector databases Comfortable with cloud (AWS preferred), CI/CD, & Git workflows Understanding of LLM security & prompt safety ? Bonus Skills (Good to Have) LoRA, QLoRA, PEFT fine-tuning Distributed training, model compression Airflow, Prefect, Dagster Terraform / CloudFormation Streamlit or Gradio Open-source contributions ? Why Join Us? Work on real-world LLM applications Exposure to advanced AI infra & MLOps Opportunity to innovate, experiment, and deploy at scale Collaborative team with strong learning culture