Job
Description
We are looking for a skilled and innovative Generative AI Developer to design, develop, and deploy AI-powered applications. The ideal candidate will have expertise in working with large language models (LLMs), Generative AI technologies, and software development, with a focus on creating impactful solutions for real-world problems. Key Responsibilities Develop and deploy AI-based applications leveraging LLMs and Generative AI models like GPT, Gemini, or similar frameworks Build scalable backend systems using Python, ensuring seamless integration with UI/UX components Design and optimize generative AI models to address diverse business challenges Fine-tune pre-trained LLMs to align with specific use cases Work closely with cross-functional teams, including data scientists, UI/UX developers, and product managers, to deliver robust solutions Collaborate with clients to gather requirements and develop customized AI capabilities Deploy solutions on cloud platforms (Azure, AWS, or GCP) and ensure system scalability and : Bachelors Degree (preferred CS/IT) in advanced analytics or ML or Master's in Machine Learning, Statistics, Econometrics, or a related field 3-10 years of professional experience in Data Science or AI/ML application development. Hands-on experience with Generative AI models and frameworks Stay updated on industry trends, emerging technologies and best practices in Gen AI & Data Skills : Proficiency in Python for application development Experience working with Generative AI frameworks and libraries (e.g., Hugging Face, OpenAI API, LangChain) Strong knowledge of LLMs and fine-tuning techniques Experience with RAG (Retrieval-Augmented Generation) techniques & Agentic workflow Hands-on experience with Python web frameworks like Flask, FastAPI, or Django Familiarity with cloud platforms (Azure, AWS, or GCP) for deployment and scaling Frontend development skills (HTML, JavaScript, React) Strong problem-solving and debugging skills Experience with version control systems such as Git/Bitbucket Understanding of MLOps frameworks for model lifecycle management Exposure to DevOps culture with hands on experience in Jenkins for CI/CD would be added advantage. Knowledge on containerization utilizing Dockers and Kubernetes will be added advantage (ref:hirist.tech) Show more Show less
