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FRONTEND DEVELOPMENT INTERN

WebBoost Solutions by UM

  • India (Remote / Multiple), India
  • Competitive Package
  • Internship
  • Posted Yesterday
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About the role

FRONTEND DEVELOPMENT INTERN

Company: WebBoost Solutions by UM

Location: Remote

Employment Type: Full-Time

Salary: Performance-Based, up to ₹25,000/-

ABOUT THE COMPANY

WebBoost Solutions by UM focuses on creating modern digital experiences and developing innovative web solutions using current technologies.

ABOUT THE ROLE

We are looking for a creative and enthusiastic Frontend Developer to build responsive, interactive, and visually appealing web interfaces while delivering smooth user experiences.

KEY RESPONSIBILITIES

  • Develop responsive web pages using HTML, CSS, and JavaScript.
  • Convert UI/UX designs into functional interfaces.
  • Build reusable components and interactive features.
  • Test websites and fix frontend issues.
  • Improve website performance and browser compatibility.
  • Collaborate with designers and developers on projects.

ELIGIBILITY

  • Degree or currently pursuing studies in Computer Science, IT, or a related field.
  • Strong interest in frontend development.
  • Freshers and experienced candidates are welcome.

REQUIRED SKILLS

  • Basic to intermediate knowledge of HTML, CSS, and JavaScript.
  • Understanding of responsive web design.
  • Familiarity with React.js and Git/GitHub.
  • Knowledge of UI/UX principles.
  • Good problem-solving and teamwork skills.

PERKS & BENEFITS

  • Performance-based salary up to ₹25,000/-.
  • Practical frontend development experience.
  • Professional guidance and industry exposure.
  • Opportunities for skill development and recognition.

EQUAL OPPORTUNITY

WebBoost Solutions by UM welcomes applicants from diverse backgrounds and promotes an inclusive environment that encourages creativity, learning, and professional growth.

Join WebBoost Solutions by UM and bring creative web experiences to life!

Eligibility & process

Who can apply

Seniority: Entry level. Employment type: Full-time

Skills & stack

JavaScript React HTML5 CSS3 Git TypeScript Next.js Tailwind CSS

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 (JavaScript, React, HTML5, CSS3, Git, TypeScript, Next.js, Tailwind CSS) & 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 WebBoost Solutions by UM 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 WebBoost Solutions by UM as a FRONTEND DEVELOPMENT INTERN?
Highlight WebBoost Solutions by UM's market reputation, recent tech innovations, and how your skills in JavaScript 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.
WebBoost Solutions by UM Competitive Package
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