Python ML /GenAI
Infosys
About the role
Strong proficiency in Python programming. Knowledge of Generative AI concepts, LLMs, and Prompt Engineering. Experience with OpenAI/Azure OpenAI APIs.
Hands-on experience with LangChain, LlamaIndex, or similar frameworks. Knowledge of RAG Architecture and vector databases such as Pinecone, ChromaDB, FAISS, or Azure AI Search. Experience with REST APIs, FastAPI, or Flask.
Understanding of Git and version control systems. Familiarity with cloud platforms such as Azure, AWS, or GCP.
Develop and maintain Generative AI applications using Python. Build AI-powered chatbots, virtual assistants, and automation solutions. Integrate Large Language Models (OpenAI, Azure OpenAI, Claude, Gemini, Llama, etc.) into applications.
Design and optimize prompts to improve model performance and accuracy. Implement Retrieval-Augmented Generation (RAG) solutions using vector databases. Work with frameworks like LangChain, LlamaIndex, and Semantic Kernel.
Develop REST APIs and integrate AI services with web applications. Collaborate with cross-functional teams to understand business requirements and deliver AI-driven solutions. Perform testing, debugging, and performance optimization of AI applications.
Eligibility & process
Who can apply
Employment type: Full-time
Skills & stack
Selection process
Details are shared by the recruiter after shortlisting.
Prep kit
19 resourcesStudy material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Technical questions 4
What is the bias-variance tradeoff and how do you prevent overfitting? Answer
Explain the difference between Precision, Recall, and F1-Score. Answer
How does Gradient Descent work and what is the role of Learning Rate? Answer
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer
Behavioural & HR questions 3
Highlight Infosys's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.