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Python ML /GenAI

Infosys

  • Bengaluru, India
  • Competitive Package
  • Fresher (0-1 Yrs)
  • Posted Yesterday
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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

Python FastAPI Flask REST APIs AWS Azure GCP Git

Selection process

Details are shared by the recruiter after shortlisting.

Prep kit

19 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Python, FastAPI, Flask, REST APIs, AWS, Azure, GCP, Git) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Infosys Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 4
What is the bias-variance tradeoff and how do you prevent overfitting? Answer
Model answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer
Model answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer
Model answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer
Model answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Behavioural & HR questions 3
Why do you want to join Infosys as a Python ML /GenAI?
Highlight Infosys's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Infosys Competitive Package
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