L #3176
Applications open
Full-Time Job
Frontend Developer
SKOOLLAGE
About the role
FRONTEND DEVELOPER
Company: SKOOLLAGE
Location: Remote
Employment Type: Full-Time
Salary: Performance-Based, up to ₹15,000/-
ABOUT THE ROLE
SKOOLLAGE is looking for a passionate Frontend Developer to create responsive, interactive, and user-friendly web interfaces.
KEY RESPONSIBILITIES
- Develop web pages using HTML, CSS, and JavaScript.
- Convert designs into functional interfaces.
- Build reusable components and interactive features.
- Fix bugs and optimize website performance.
- Ensure mobile responsiveness and browser compatibility.
ELIGIBILITY
- Degree or currently pursuing studies in IT, Computer Science, or a related field.
- Strong interest in frontend development.
- Freshers and experienced candidates can apply.
REQUIRED SKILLS
- Knowledge of HTML, CSS, and JavaScript.
- Understanding of responsive web design.
- Familiarity with React.js and Git/GitHub.
- Good problem-solving and teamwork skills.
PERKS & BENEFITS
- Performance-based salary up to ₹15,000/-.
- Real-world project experience.
- Professional guidance and skill development.
- Industry exposure and performance recognition.
Join SKOOLLAGE and build engaging digital experiences!
Eligibility & process
Who can apply
Seniority: Entry level. Employment type: Full-time
Skills & stack
Selection process
Details are shared by the recruiter after shortlisting.
Prep kit
19 resourcesStudy material 4
Aptitude Practice Questions & Mock Tests
Curated logical, quantitative, and verbal reasoning problems for the initial online screening round.
Company-Specific Interview Preparation Corner
Detailed interview experiences, exam formats, and previous test questions for SKOOLLAGE and tech roles.
Technical Placement Question Bank
High-yield coding cheat sheets, core CS fundamentals (OOP, DBMS, OS, Networks), and rapid revision guides.
Algorithm, DSA & Live Code Debugger Practice
Hands-on problem sets to improve coding speed and step-by-step memory debugging.
Company-specific guides 4
APTITUDE & LOGIC
Aptitude Practice Questions & Online Mock Tests
Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.
COMPANY GUIDE
SKOOLLAGE Interview Preparation Corner
Comprehensive guide covering typical interview formats, common questions, and preparation tips for SKOOLLAGE and off-campus tech roles.
MOCK TESTS & PAPERS
Comprehensive Interview Prep Resources & Syllabus
Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.
CODING PRACTICE
Algorithm and Data Structure Problem Set
Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.
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
SKOOLLAGE 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 SKOOLLAGE as a Frontend Developer?
Highlight SKOOLLAGE's market reputation, recent tech innovations, and how your skills in JavaScript directly solve their team's objectives.
Highlight SKOOLLAGE'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).
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.
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Competitive Package
India (Remote / Multiple), India
Seniority: Entry level. Employment type: …
