About the role
Primary Roles & Responsibilities
· Design and implement GenAI solutions leveraging LLMs, RAG pipelines, and Agentic AI architectures.
· Develop and fine-tune deep learning models for NLP tasks using frameworks like PyTorch or TensorFlow.
· Build scalable APIs using FastAPI to serve AI models and integrate with enterprise systems.
· Collaborate with data scientists and ML engineers to deploy models using CI/CD pipelines on Azure.
· Optimize model performance and ensure robustness in production environments.
· Stay updated with the latest research and advancements in generative AI and deep learning.
· Scalability & Performance: Ability to write efficient code and consider scalability and latency implications for Gen AI applications.
· Containerization: Practical experience with Docker for packaging and deploying applications.
Must Have
· Strong programming skills in Python with experience in building ML/NLP applications.
· Hands-on experience with Deep Learning, Machine Learning, and Natural Language Processing.
· Proficiency in working with LLMs (e.g., GPT,Gemini, LLaMA, Mistral) and RAG architecture.
· Experience with Agentic AI frameworks and autonomous agent design.
· Familiarity with FastAPI for building RESTful APIs.
· Experience with CI/CD pipelines and deploying solutions on Azure Cloud, GCP and AWS
· Solid understanding of data structures, algorithms, and software engineering principles.
· Bachelor’s or master’s degree in computer science, AI, Data Science, or related field.
Good TO Have
· Excellent Communication Skills
· Strong Software Engineering Background (Productionizing the models)
· Hands-on experience with data science tools
· Problem-solving aptitude
· Analytical mind and great business sense