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Applications open Full-Time Job

MERN STACK DEVELOPER

SKOOLLAGE

  • India (Remote / Multiple), India
  • Competitive Package
  • Fresher (0-1 Yrs)
  • Posted Today
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About the role

MERN STACK DEVELOPER

Company: SKOOLLAGE

Location: Remote

Employment Type: Full-Time

Compensation: Performance-Based, up to ₹30,000/-

ABOUT THE COMPANY

SKOOLLAGE is a technology-driven organization focused on building modern digital platforms and innovative web solutions. The company aims to create scalable, efficient, and user-friendly applications that enhance digital experiences.

ABOUT THE ROLE

SKOOLLAGE is looking for a passionate and technically skilled MERN Stack Developer to develop and maintain dynamic web applications. The selected candidate will work across frontend and backend technologies, build APIs, manage databases, and deliver reliable and scalable web solutions.

KEY RESPONSIBILITIES

  • Develop and maintain applications using the MERN stack.
  • Build responsive interfaces using React.js.
  • Develop backend services using Node.js and Express.js.
  • Manage databases and application data using MongoDB.
  • Create and integrate REST APIs.
  • Debug and resolve technical issues.
  • Optimize application performance and functionality.
  • Maintain clean, reusable, and scalable code.
  • Collaborate with the team on development projects.
  • Assist with application testing and deployment.

ELIGIBILITY

  • Bachelor's degree in Computer Science, IT, or a related field.
  • Freshers and experienced candidates are welcome.
  • Understanding of frontend and backend development.
  • Strong interest in modern web technologies.
  • Ability to work independently and meet deadlines.

REQUIRED SKILLS

  • HTML, CSS, and JavaScript.
  • React.js and component-based development.
  • Node.js and Express.js.
  • MongoDB and database management.
  • REST APIs and API integration.
  • Git and GitHub.
  • Strong debugging and problem-solving abilities.
  • Good communication and teamwork skills.

PERKS & BENEFITS

  • Performance-based compensation up to ₹30,000/-.
  • Opportunity to work on real-world development projects.
  • Professional growth and career development.
  • Exposure to modern technologies and tools.
  • Collaborative work environment.
  • Recognition for outstanding contributions.

EQUAL OPPORTUNITY

SKOOLLAGE is committed to creating an inclusive and supportive workplace. We welcome candidates from diverse backgrounds who are passionate about coding, innovation, and building impactful digital solutions.

Ready to build the next generation of web applications? Join SKOOLLAGE and grow with us!

Eligibility & process

Who can apply

Seniority: Entry level. Employment type: Full-time

Skills & stack

JavaScript React Next.js HTML5 CSS3 Node.js Express.js REST APIs

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, Next.js, HTML5, CSS3, Node.js, Express.js, REST APIs) & 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 MERN STACK DEVELOPER?
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).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
SKOOLLAGE Competitive Package
Recruiter Resume Apply
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