KASHII UPDATEZ Everyday Student Requirements & Python Coding Tutorials by Python Kashi
REQUIREMENT_ID_1821 β€’ 3-DAY_ACTIVE_POLICY

Software Engineer Trainee (AI + Full Stack)

Company
Company Google
Type
Opportunity Type Internship
Salary
Stipend / Salary 7–9 LPA
Location
Location Remote
Posted Date
Posted Date Yesterday
JavaScript React.js Node.js REST APIs Git Database fundamentals AI/ML concepts Problem solving Communication Eagerness to learn
πŸ“–
Placement Papers Collection Open Resource β†—
Curated set of placement papers that help candidates practice typical questions asked in tech interviews.
πŸ“–
Recruitment Process Experiences Open Resource β†—
First‑hand accounts of candidates who have gone through the recruitment journey, useful for understanding interview flow.
πŸ“–
Interview Preparation Guide Open Resource β†—
Comprehensive guide covering topics, sample questions, and preparation tips for tech interviews.
πŸ“–
Algorithm Problem Set Open Resource β†—
Extensive library of algorithmic problems to sharpen coding skills required for technical rounds.

Graduates with a Bachelor’s degree in Engineering (any branch) from the 2025, 2026 or 2027 batch. Minimum aggregate of 60% (or CGPA 6.0/10). No active backlogs at the time of joining. Must have a stable internet connection for remote work and be eligible to work from home in India.

1
Round 1: Application shortlisting
2
Round 2: Online technical assessment
3
Round 3: Technical interview (coding & system design)
4
Round 4: HR interview
RadialBrain is an emerging technology startup that focuses on building intelligent web solutions for enterprises across India. Founded by a group of AI enthusiasts and full‑stack engineers, the company blends cutting‑edge machine‑learning models with modern web frameworks to deliver products that automate business workflows, enhance user experiences, and unlock data‑driven insights. Although headquartered in Bengaluru, RadialBrain operates with a fully distributed model, allowing talent from any part of the country to contribute to its product roadmap. The firm’s culture emphasizes rapid learning, ownership, and a collaborative spirit, encouraging fresh engineers to experiment with new tools and take responsibility for end‑to‑end feature delivery. The role of Software Engineer Trainee (AI + Full Stack) is designed specifically for recent engineering graduates who are eager to dive into both front‑end development and AI integration. As a trainee, you will work under senior engineers, gaining hands‑on experience in building responsive user interfaces, designing RESTful services, and embedding AI APIs that power features such as recommendation engines, image classification, and automated content generation. The position offers a clear growth path: high‑performing trainees can transition to full‑fledged Software Engineer roles within six months, later moving into specialist tracks like AI Engineer, Front‑End Lead, or DevOps Engineer depending on interest and performance. **Key Responsibilities** 1. Design, develop, and maintain scalable full‑stack web applications using React.js and Node.js/Express. 2. Implement responsive UI components, ensuring cross‑browser compatibility and accessibility. 3. Build and expose REST APIs that interact with databases such as MySQL or MongoDB. 4. Integrate third‑party AI services (e.g., Google Cloud AI, OpenAI) and develop custom model inference pipelines. 5. Write unit, integration, and end‑to‑end tests to guarantee code quality and reliability. 6. Participate in code reviews, contribute to the team’s coding standards, and document technical decisions. 7. Debug production issues, optimise performance, and monitor application health. 8. Collaborate with product managers, designers, and data scientists to translate requirements into technical solutions. 9. Stay updated with emerging technologies in AI, cloud services, and modern JavaScript frameworks. 10. Contribute to automation scripts that streamline CI/CD pipelines and deployment workflows. **Tech Stack**: JavaScript, TypeScript, React.js, Node.js/Express, RESTful APIs, Git, Docker, AWS/GCP, MySQL/MongoDB, AI/ML APIs. **Why Join RadialBrain?** The trainee program offers a rare blend of AI exposure and full‑stack craftsmanship, backed by mentorship from industry veterans. With a competitive CTC of 7–9β€―LPA, flexible remote work, and a culture that rewards curiosity, fresh engineers can accelerate their careers while contributing to real‑world AI‑driven products. Overall, this opportunity is ideal for candidates who love building end‑to‑end solutions, are fascinated by AI, and thrive in a remote, fast‑paced startup environment.

Google β€” AI & Machine Learning Interview Guide

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

APTITUDE & LOGIC πŸ“–
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 β†—
COMPANY GUIDE 🎯
Google Interview Preparation Corner

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

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

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

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

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

Open Resource β†—
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.js, Node.js, REST APIs, Git, Database fundamentals, AI/ML concepts, Problem solving, Communication, Eagerness to learn) & 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
Google 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 β–Ό
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 β–Ό
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 β–Ό
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 β–Ό
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 Google as a Software Engineer Trainee (AI + Full Stack)?
Preparation Tip: Highlight Google'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.
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.

More Fresh Requirements in Software Engineering

View Category Feed β†—
Google
Software Engineer Trainee (AI + Full Stack)
Apply Apply Now β†—
Chat Chat with Kashii