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REQUIREMENT_ID_353 • 3-DAY_ACTIVE_POLICY

AI/ML Engineer (0-1 years)

Company
Company Cyncly
Type
Opportunity Type Internship
Salary
Stipend / Salary Not disclosed
Location
Location Bengaluru, Karnataka, India
Posted Date
Posted Date Today
Python TensorFlow PyTorch OpenCV Pillow scikit‑image SQL REST API Azure DevOps vector database deep learning computer vision problem solving communication
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Helps candidates prepare for technical interviews and coding challenges relevant to AI/ML roles.
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Provides real interview questions and experiences to understand the hiring process and common topics.
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Recruitment Process Overview Open Resource ↗
Offers guidance on the steps, expectations, and best practices for the recruitment journey.
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Coding Problem Repository Open Resource ↗
A collection of coding problems to sharpen algorithmic thinking and problem‑solving skills.

Bachelor’s or Master’s degree in Computer Science, MCA, AI, or related fields. 0‑1 year of experience in AI/ML. Strong academic record (minimum 60% or equivalent). No backlog policy. Excellent analytical, problem‑solving, and communication skills required.

1
Round 1: Technical coding and AI/ML concepts
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Round 2: System design and project discussion
3
Round 3: HR interview
Cyncly is a global technology powerhouse with over 2,800 employees and 70,000 customers spanning more than 100 countries. The company specializes in end‑to‑end software solutions that connect designers, retailers, and manufacturers to the world’s largest repository of product content. With a presence in North & South America, Europe, Asia Pacific, and Africa, Cyncly serves industries such as Kitchen & Bath, Furniture, Window, Glass & Door, and Flooring. The firm has a rich history of 30+ years and is backed by leading growth private equity firms, positioning it for continued organic expansion and strategic acquisitions. The AI/ML Engineer role is situated within Cyncly’s AI Center of Innovation. Freshers with 0‑1 year of experience will be tasked with designing, implementing, and deploying state‑of‑the‑art AI and computer vision solutions that power the company’s product suite. The engineer will build RESTful APIs to expose AI models, design vector database schemas, and collaborate closely with data scientists, data engineers, and DevOps teams to ensure scalable, secure, and high‑performance deployments. Key Responsibilities (8‑10 points): 1. Design and develop AI/ML models using TensorFlow, PyTorch, and OpenCV for computer vision tasks. 2. Build and expose REST APIs that integrate AI model outputs into client applications. 3. Design vector database schemas and write efficient, scalable queries for similarity search. 4. Create rapid proof‑of‑concepts to showcase technology capabilities to stakeholders. 5. Build and maintain CI/CD pipelines using Azure DevOps, ensuring continuous integration and deployment. 6. Collaborate with DevOps engineers to configure secure, highly scalable cloud environments. 7. Conduct code reviews, enforce coding standards, and mentor interns/freshers. 8. Troubleshoot and debug production issues, providing both tactical and permanent solutions. 9. Stay updated on emerging AI/ML research, especially in generative AI and computer vision. 10. Document technical designs and maintain up‑to‑date system documentation. Tech Stack: Python, TensorFlow, PyTorch, OpenCV, Pillow, scikit‑image, SQL, REST API design, Azure DevOps, vector databases (e.g., Pinecone, Milvus), cloud platforms. Growth Path: Freshers start by contributing to small modules and POCs, then progress to full‑stack AI solution development, and eventually lead AI initiatives, mentor juniors, and shape product strategy. The company’s culture of continuous learning and cross‑functional collaboration accelerates career growth. Why Join Cyncly? The firm’s global footprint, commitment to AI innovation, and inclusive “OneCyncly” culture provide a stimulating environment for early‑career engineers. Employees enjoy flexible work arrangements, exposure to cutting‑edge technology, and the chance to impact millions of customers worldwide.

Cyncly — Data Analytics & SQL Interview Guide

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

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.

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COMPANY GUIDE 🎯
Cyncly Interview Preparation Corner

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

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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.

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CODING PRACTICE 💻
Algorithm and Data Structure Problem Set

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

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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, TensorFlow, PyTorch, OpenCV, Pillow, scikit‑image, SQL, REST API, Azure DevOps, vector database, deep learning, computer vision, problem solving, communication) & 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
Cyncly Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between WHERE and HAVING clauses in SQL? Answer ▼
Model Answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer ▼
Model Answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer ▼
Model Answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer ▼
Model Answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer ▼
Model Answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Why do you want to join Cyncly as a AI/ML Engineer (0-1 years)?
Preparation Tip: Highlight Cyncly'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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