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REQUIREMENT_ID_1370 โ€ข 3-DAY_ACTIVE_POLICY

Associate AI Forward Deployed Engineer (AI FDE)

Company
Company yottaflex.ai
Type
Opportunity Type Internship
Salary
Stipend / Salary โ‚น7 LPA (CTC) after internship, โ‚น20,000 per month stipend during internship
Location
Location Hyderabad, Telangana
Posted Date
Posted Date Today
Python Generative AI Large Language Models AI APIs Backend Development FastAPI Flask Git GitHub Problem Solving Debugging API Integration
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Aptitude Practice Questions Open Resource โ†—
Helps you sharpen quantitative and logical reasoning skills essential for the initial screening test.
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Technical Interview Preparation Guide Open Resource โ†—
Covers common coding patterns, data structures, and AI fundamentals frequently asked in technical rounds.
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Comprehensive Interview Resources Open Resource โ†—
Provides curated interview experiences, sample questions, and tips to boost confidence for YottaFlex interviews.
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Algorithm Practice Platform Open Resource โ†—
Offers a vast collection of coding problems to practice and improve problemโ€‘solving speed for the coding test.

Graduates (B.Tech/B.E., B.Sc., M.Tech, M.Sc.) in Computer Science, Information Technology, Electronics, or related streams; minimum 60% aggregate (or CGPA 6.5/10); no active backlogs at the time of joining; batch years 2022โ€‘2026 acceptable; strong academic record and demonstrable project work in AI/ML preferred.

1
Round 1: Online coding test (DSA & Python)
2
Round 2: Technical interview (AI concepts, project discussion, system design)
3
Round 3: HR interview (fitment, communication, expectations)
YottaFlex is an emerging AIโ€‘driven technology firm headquartered in Hyderabad, Telangana. The company focuses on delivering endโ€‘toโ€‘end artificialโ€‘intelligence solutions for enterprises across sectors such as finance, healthcare, logistics, and retail. With a fastโ€‘growing client base and a culture that encourages rapid prototyping, YottaFlex aims to bridge the gap between cuttingโ€‘edge research and realโ€‘world business impact. The organization invests heavily in talent development, offering handsโ€‘on exposure to the latest generativeโ€‘AI models, cloud platforms, and product engineering practices. The role of Associate AI Forward Deployed Engineer (AI FDE) is designed for fresh graduates and earlyโ€‘career professionals who are passionate about turning AI concepts into deployable applications. As an AI FDE, you will work directly with client teams to understand their business challenges, design AIโ€‘powered solutions, and deliver functional prototypes that can be scaled into production systems. You will be mentored by senior AI engineers and will get the opportunity to experiment with large language models, vision APIs, and custom model pipelines while learning best practices for software engineering and DevOps. Key Responsibilities: 1. Gather and analyse client requirements to translate business problems into AI solution specifications. 2. Design, develop, and test AI prototypes using Python, LLMs, and generativeโ€‘AI frameworks. 3. Integrate AI models and thirdโ€‘party APIs into backend services and userโ€‘facing applications. 4. Write clean, modular code and maintain version control using Git and GitHub. 5. Conduct debugging, performance tuning, and iterative improvements on AI applications. 6. Collaborate with crossโ€‘functional engineering teams to ensure seamless deployment and scalability. 7. Prepare technical documentation, demo presentations, and client handโ€‘over materials. 8. Stay updated with emerging AI research, tools, and industry trends to propose innovative solutions. 9. Participate in code reviews and contribute to the teamโ€™s knowledge base. 10. Assist in postโ€‘deployment monitoring and support to ensure solution reliability. Tech Stack: Python, PyTorch/TensorFlow, LangChain, OpenAI/Claude APIs, FastAPI/Flask, Docker, Git, CI/CD pipelines, cloud services (AWS/GCP/Azure). Growth Path: Starting as an Associate AI FDE, high performers can progress to Senior AI Engineer, AI Solutions Architect, or Product Lead within 2โ€‘3 years, with opportunities to lead client engagements and mentor new hires. Why Join YottaFlex? The company offers a paid 6โ€‘month internship with a stipend of โ‚น20,000 per month, followed by a fullโ€‘time CTC of โ‚น7โ€ฏLPA. You will work on live client projects, gain exposure to stateโ€‘ofโ€‘theโ€‘art AI technologies, and be part of a collaborative, innovationโ€‘focused environment that values continuous learning and career advancement.

yottaflex.ai โ€” AI & Machine Learning Interview Guide

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

APTITUDE & LOGIC ๐Ÿ“–
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 โ†—
COMPANY GUIDE ๐ŸŽฏ
yottaflex.ai Interview Preparation Corner

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

Open Resource โ†—
MOCK TESTS & PAPERS ๐Ÿ“
Comprehensive Interview Prep Resources & Syllabus

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

Open Resource โ†—
CODING PRACTICE ๐Ÿ’ป
Algorithm and Data Structure Problem Set

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

Open Resource โ†—
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, Generative AI, Large Language Models, AI APIs, Backend Development, FastAPI, Flask, Git, GitHub, Problem Solving, Debugging, API Integration) & 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
yottaflex.ai 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 โ–ผ
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 โ–ผ
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 โ–ผ
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 โ–ผ
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 yottaflex.ai as a Associate AI Forward Deployed Engineer (AI FDE)?
Preparation Tip: Highlight yottaflex.ai'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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