Job
Description
Job Summary: We are looking for a highly skilled and innovative Python Developer with strong experience in Generative AI to design, develop, and deploy intelligent applications that leverage cutting-edge AI/ML technologies. The ideal candidate should be proficient in Python programming and have hands-on experience with modern Gen AI tools and frameworks (like GPT, LLMs, Diffusion Models). You will collaborate closely with cross-functional teams to deliver robust, scalable, and intelligent solutions. Key Responsibilities: Develop and maintain AI-powered applications using Python and modern Gen AI tools (OpenAI, Hugging Face, LangChain, etc.). Design and implement intelligent agents, data pipelines, and LLM-based applications. Fine-tune and deploy large language models (LLMs) for specific business use cases. Collaborate with data scientists, product managers, and designers to integrate AI capabilities into existing and new systems. Build RESTful APIs and backend services that leverage Gen AI components. Optimize application performance and manage infrastructure on cloud platforms (AWS, GCP, or Azure). Ensure code quality, security, and best practices in AI development. Stay current with advances in AI/ML and contribute to innovation within the team. Required Qualifications: Bachelors or Master’s degree in Computer Science, AI/ML, or related field from a Tier 1 institution. 6+ years of software development experience, with strong proficiency in Python. Hands-on experience with LLMs, prompt engineering, and fine-tuning. Experience with frameworks like Hugging Face Transformers, LangChain, or OpenAI API. Solid understanding of data structures, algorithms, and API development. Familiarity with ML pipelines, model deployment, and vector databases (like FAISS, Pinecone, or Weaviate). Knowledge of cloud platforms and containerization (Docker, Kubernetes). Ability to work in agile, fast-paced environments and drive projects from concept to production. Preferred Qualifications: Contributions to open-source Gen AI or ML projects. Experience with RAG (Retrieval-Augmented Generation) pipelines. Knowledge of NLP, computer vision, or multi-modal AI systems. Familiarity with MLOps and AI observability tools. Published research papers or blogs on AI/ML topics.
