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REQUIREMENT_ID_362 β€’ 3-DAY_ACTIVE_POLICY

Gen AI Developer Associate

Company
Company Hexaware Technologies
Type
Opportunity Type Internship
Salary
Stipend / Salary 3.5 LPA
Location
Location India
Posted Date
Posted Date Today
Python TensorFlow PyTorch scikit-learn Natural Language Processing Generative AI Machine Learning Data Preprocessing Feature Engineering Linear Algebra Probability Statistics
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Aptitude and Reasoning Practice Set Open Resource β†—
Helps candidates sharpen quantitative and logical reasoning skills required for Hexaware's online assessment.
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Hexaware Recruitment Experience Guide Open Resource β†—
Provides insights into Hexaware's interview process, question patterns, and preparation tips.
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Comprehensive Interview Preparation Hub Open Resource β†—
Offers curated notes, mock interviews, and topic-wise study plans useful for Hexaware interviews.
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Coding Practice Problem Set Open Resource β†—
Contains a wide range of algorithmic problems to improve coding speed and accuracy for Hexaware's technical round.

Bachelor’s degree in Computer Science, Information Technology, Mathematics, Engineering or related field; strong foundation in mathematics and programming.

1
Round 1: Online Assessment (aptitude + coding)
2
Round 2: Technical Interview (ML/NLP concepts, coding)
3
Round 3: HR Interview (fit, motivations, salary expectations)
Hexaware Technologies is a global leader in next‑generation digital solutions, serving Fortune 500 clients across banking, insurance, healthcare, and manufacturing. With a strong focus on automation, cloud, and AI, the company has built a reputation for delivering innovative, end‑to‑end services that help enterprises accelerate their digital transformation journeys. Hexaware’s culture emphasizes continuous learning, collaborative problem‑solving, and a commitment to sustainability, making it an attractive destination for fresh talent looking to grow in a technology‑driven environment. The Gen AI Developer Associate role is designed for recent graduates or professionals with up to one year of experience who are eager to dive into the fast‑evolving world of generative artificial intelligence. As a member of the AI Solutions team, you will work alongside senior engineers and data scientists to design, develop, and deploy cutting‑edge generative models that power real‑world applications such as chatbots, content creation tools, and intelligent assistants. This position offers a unique blend of hands‑on coding, research, and product deployment, providing a solid foundation for a long‑term career in AI. Key Responsibilities: 1. Design, implement, and fine‑tune machine‑learning models with a focus on generative AI and natural language processing. 2. Perform data preprocessing, cleaning, and feature engineering to prepare high‑quality training datasets. 3. Conduct experiments to evaluate model performance using metrics such as BLEU, ROUGE, and perplexity. 4. Stay updated with the latest research papers and industry trends in generative AI, proposing innovative solutions. 5. Write clean, modular, and well‑documented Python code adhering to best practices. 6. Collaborate with cross‑functional teams to integrate AI models into production pipelines and APIs. 7. Assist in deploying models on cloud platforms (AWS, Azure) and monitor their performance post‑deployment. 8. Participate in code reviews, knowledge‑sharing sessions, and internal hackathons. 9. Contribute to the creation of technical documentation and user guides for AI solutions. 10. Provide support for troubleshooting and optimizing models in live environments. Tech Stack: Python, TensorFlow, PyTorch, scikit‑learn, Hugging Face Transformers, Docker, Kubernetes, AWS/Azure, Git, SQL/NoSQL databases. Growth Path: Starting as an Associate, you can progress to AI Engineer, Senior AI Engineer, and eventually AI Architect or Product Lead, with opportunities to specialize in research, solution architecture, or product management. Why Join Hexaware? The company offers a vibrant learning ecosystem, mentorship from industry experts, and exposure to large‑scale AI projects. Employees benefit from flexible work arrangements, competitive compensation, and a clear career progression roadmap, making Hexaware an ideal launchpad for aspiring AI professionals.

Hexaware Technologies β€” AI & Machine Learning Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC πŸ“–
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource β†—
COMPANY GUIDE 🎯
Hexaware Technologies Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Hexaware Technologies and off-campus tech roles.

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource β†—
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, TensorFlow, PyTorch, scikit-learn, Natural Language Processing, Generative AI, Machine Learning, Data Preprocessing, Feature Engineering, Linear Algebra, Probability, Statistics) & 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
Hexaware Technologies Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the bias-variance tradeoff and how do you prevent overfitting? Answer β–Ό
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 β–Ό
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 β–Ό
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 β–Ό
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).
Why do you want to join Hexaware Technologies as a Gen AI Developer Associate?
Preparation Tip: Highlight Hexaware Technologies'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.
Preparation Tip: 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?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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