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REQUIREMENT_ID_1997 • 3-DAY_ACTIVE_POLICY JD

AI Engineer – Intern

Company
Company E2M Solutions
Type
Opportunity Type Internship
Salary
Stipend / Salary ₹15,000 per month stipend; potential full‑time CTC ₹3–4 LPA after conversion
Location
Location Ahmedabad, India
Posted Date
Posted Date Yesterday
Apply on Official Website ↗
Python REST APIs HTML CSS JavaScript AI/ML fundamentals Large Language Models Database fundamentals CRUD operations Basic backend development
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Aptitude Practice Questions Open Resource ↗
Curated quantitative and logical reasoning problems to sharpen problem‑solving speed for the virtual assessment stage.
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Company Interview Preparation Guide Open Resource ↗
General interview tips and common question patterns that help candidates prepare for technical and HR rounds at tech firms like E2M.
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Comprehensive Interview Prep Resource Open Resource ↗
A collection of coding, system design, and AI‑focused interview resources useful for the technical interview.
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Algorithm and Data Structure Problem Set Open Resource ↗
Practice problems on coding platforms to improve coding efficiency and accuracy, essential for the technical assessment.

Eligible degrees: B.Tech / BE, M.Tech / ME, MCA, BCA. Eligible branches: Computer Science Engineering, Information Technology, BCA, MCA. Pass‑out batches: 2025, 2026, 2027. No minimum percentage requirement mentioned. Preference for candidates residing in Ahmedabad. No explicit backlog policy stated; assume standard campus eligibility (max 2 backlogs).

1
Round 1: Virtual Assessment
2
Round 2: Technical Interview (in‑person, Ahmedabad)
3
Round 3: HR Round
E2M Solutions is a fast‑growing technology services firm headquartered in Ahmedabad, Gujarat. The company specializes in delivering end‑to‑end AI and software solutions for clients across fintech, healthcare, and e‑commerce domains. With a strong focus on research‑driven product development, E2M has built a reputation for fostering innovation through collaborative teams and a culture that encourages continuous learning. Over the past few years, the firm has expanded its AI practice, integrating large language models (LLMs) and generative AI into real‑world applications, positioning itself as a go‑to partner for businesses looking to modernize their digital offerings. The AI Engineer – Intern role is designed for fresh graduates who are eager to translate theoretical AI knowledge into production‑grade solutions. Interns will work side‑by‑side with senior AI engineers and product managers, contributing to the design, development, and deployment of AI‑powered web applications. The position offers a six‑month paid internship with a clear pathway to a full‑time role, making it an ideal launchpad for a career in artificial intelligence and software engineering. Key Responsibilities: 1. Design and implement Python‑based AI modules that interact with LLM APIs such as OpenAI, Claude, or Gemini. 2. Develop and expose RESTful services using FastAPI or Flask to enable front‑end consumption. 3. Build responsive web interfaces with HTML, CSS, and JavaScript (or React/Next.js) to showcase AI features. 4. Perform CRUD operations on relational databases like PostgreSQL and cloud databases such as Supabase or Firebase. 5. Integrate vector databases and embeddings for Retrieval‑Augmented Generation (RAG) pipelines. 6. Write clean, version‑controlled code using Git and collaborate via GitHub pull‑requests. 7. Conduct unit testing, debugging, and performance profiling of AI workflows. 8. Document technical designs, API specifications, and deployment procedures. 9. Participate in code reviews and knowledge‑sharing sessions within the AI team. 10. Explore and prototype emerging AI agents and prompt‑engineering techniques. Tech Stack: Python, FastAPI/Flask, React/Next.js, LangChain/LangGraph, OpenAI/Claude/Gemini APIs, PostgreSQL, Supabase/Firebase, Git, Docker (optional). Growth Path: The internship serves as a talent pipeline for a full‑time AI Engineer position (CTC ₹3–4 LPA). Successful interns receive mentorship, exposure to live client projects, and opportunities to lead small modules, accelerating their professional development. Why Join E2M Solutions? You will gain hands‑on experience with cutting‑edge generative AI tools, work in a collaborative office environment in Ahmedabad, receive a competitive stipend, and have a clear conversion route to a permanent role. The company’s emphasis on learning, mentorship, and real‑world impact makes it an excellent place to start a career in AI engineering.

E2M Solutions — AI & Machine Learning Interview Guide

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

APTITUDE & LOGIC šŸ“–
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 ↗
COMPANY GUIDE šŸŽÆ
E2M Solutions Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for E2M Solutions and off-campus tech roles.

Open Resource ↗
MOCK TESTS & PAPERS šŸ“
Comprehensive Interview Prep Resources & Syllabus

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

Open Resource ↗
CODING PRACTICE šŸ’»
Algorithm and Data Structure Problem Set

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

Open Resource ↗
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, REST APIs, HTML, CSS, JavaScript, AI/ML fundamentals, Large Language Models, Database fundamentals, CRUD operations, Basic backend development) & 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
E2M Solutions 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 ā–¼
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 ā–¼
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 ā–¼
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 ā–¼
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 E2M Solutions as a AI Engineer – Intern?
Preparation Tip: Highlight E2M Solutions'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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