Python Developer with AI & LLM Exp-Full time-Hybrid

We are seeking a highly skilled Python LLM Developer with expertise in Generative AI, Large Language Models (LLMs), Machine Learning, and API integration. The ideal candidate will be responsible for developing AI-powered applications, integrating LLM solutions, fine-tuning models, and building scalable backend services using Python and FastAPI.

Key Responsibilities

• Design, develop, and deploy AI-powered applications using Python and LLM technologies.
• Build scalable APIs and backend services using FastAPI.
• Integrate Large Language Models (LLMs) and Generative AI services into enterprise applications.
• Develop data processing, transformation, and preprocessing pipelines.
• Fine-tune and optimize machine learning and deep learning models for specific business use cases.
• Implement Retrieval-Augmented Generation (RAG) and prompt engineering solutions.
• Collaborate with data scientists, AI engineers, and business stakeholders to deliver AI-driven solutions.
• Optimize model performance, inference speed, and scalability.
• Develop and maintain reusable AI components and services.
• Participate in code reviews, testing, deployment, and production support activities.

Required Skills & Qualifications

• 5+ years of experience in Python development.
• Strong expertise in:
  • Python
  • FastAPI
  • REST APIs
  • Object-Oriented Programming (OOP)
• Strong understanding of:
  • Large Language Models (LLMs)
  • Generative AI
  • Machine Learning
  • Deep Learning
• Experience with:
  • Pandas
  • NumPy
  • Scikit-learn
• Knowledge of:
  • Data Collection
  • Data Preprocessing
  • Feature Engineering
  • Model Evaluation
• Experience integrating AI services through APIs.
• Strong understanding of software engineering best practices.
• Excellent analytical and problem-solving skills.

Preferred Skills

• Experience with deep learning frameworks:
  • PyTorch
  • TensorFlow
  • Keras
• Hands-on experience with:
  • OpenAI APIs
  • LangChain
  • LlamaIndex
  • Hugging Face
  • Vector Databases
• Experience implementing:
  • RAG (Retrieval-Augmented Generation)
  • Prompt Engineering
  • AI Agents
  • Conversational AI Solutions
• Knowledge of Docker, Kubernetes, and cloud platforms (AWS, Azure, or Google Cloud Platform).
• Familiarity with CI/CD pipelines and DevOps practices.