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Pyhton Gen AI Developer
Pyhton Gen AI DeveloperArcitech • India
Pyhton Gen AI Developer

Pyhton Gen AI Developer

Arcitech • India
12 hours ago
Job description

Pyhton Gen AI Developer

Your Responsibilities

  • Develop, train, and optimize ML models using PyTorch, TensorFlow, and Keras.
  • Build end-to-end LLM and RAG pipelines using LangChain and LangGraph.
  • Work with LLM APIs (OpenAI, Anthropic Claude, Azure OpenAI) and implement prompt engineering strategies.
  • Utilize Hugging Face Transformers for model fine-tuning and deployment.
  • Integrate embedding models for semantic search and retrieval systems.
  • Work with transformer-based architectures (BERT, GPT, LLaMA, Mistral) for production use cases.
  • Implement LLM evaluation frameworks (RAGAS, LangSmith) and performance optimization.
  • Implement real-time communication with FastAPI WebSockets.
  • Implement pgvector for embedding storage and similarity search with efficient indexing strategies.
  • Integrate vector databases (pgvector, Pinecone, Weaviate, FAISS, Milvus) for retrieval pipelines.
  • Containerize AI services with Docker and deploy on Kubernetes (EKS / GKE / AKS).
  • Configure AWS infrastructure (EC2, S3, RDS, SageMaker, Lambda, CloudWatch) for AI / ML workloads.
  • Version ML experiments using MLflow, Weights & Biases, or Neptune.
  • Deploy models using serving frameworks (TorchServe, BentoML, TensorFlow Serving).
  • Implement model monitoring, drift detection, and automated retraining pipelines.
  • Build CI / CD pipelines for automated testing and deployment with ≥80% test coverage (pytest).
  • Follow security best practices for AI systems (prompt injection prevention, data privacy, API key management).
  • Participate in code reviews, tech talks, and AI learning sessions.
  • Follow Agile / Scrum methodologies and Git best practices.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, AI / ML, or related field.
  • 2–5 years of Python development experience (Python 3.9+) with strong AI / ML background.
  • Hands-on experience with LangChain and LangGraph for building LLM-powered workflows and RAG systems.
  • Deep learning experience with PyTorch or TensorFlow.
  • Experience with Hugging Face Transformers and model fine-tuning.
  • Proficiency with LLM APIs (OpenAI, Anthropic, Azure OpenAI) and prompt engineering.
  • Strong experience with FastAPI frameworks.
  • Proficiency in PostgreSQL with pgvector extension for embedding storage and similarity search.
  • Experience with vector databases (pgvector, Pinecone, Weaviate, FAISS, or Milvus).
  • Experience with model versioning tools (MLflow, Weights & Biases, or Neptune).
  • Skilled in Git workflows, automated testing (pytest), and CI / CD practices.
  • Understanding of security principles for AI systems.
  • Excellent communication and analytical thinking.
  • Nice to Have

  • Experience with multiple vector databases (Pinecone, Weaviate, FAISS, Milvus).
  • Knowledge of advanced LLM fine-tuning (LoRA, QLoRA, PEFT) and RLHF.
  • Experience with model serving frameworks and distributed training.
  • Familiarity with workflow orchestration tools (Airflow, Prefect, Dagster).
  • Knowledge of quantization and model compression techniques.
  • Experience with infrastructure as code (Terraform, CloudFormation).
  • Familiarity with data versioning tools (DVC) and AutoML.
  • Experience with Streamlit or Gradio for ML demos.
  • Background in statistics, optimization, or applied mathematics.
  • Contributions to AI / ML or LangChain / LangGraph open-source projects.
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