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REQUIREMENT_ID_2152 • 3-DAY_ACTIVE_POLICY JD

AI Engineering Intern

Company
Company Amber
Type
Opportunity Type Internship
Salary
Stipend / Salary Rs 15,000 per month
Location
Location Pune, India
Posted Date
Posted Date Today
Apply on Official Website ↗ šŸ¤ Connect Recruiter ↗
AM
Amber Technical Recruiter
Talent Acquisition Partner
šŸ¢ Amber • Direct Recruiter Email: recruiter@amber.com
Python Machine Learning Deep Learning Data Preprocessing SQL Git TensorFlow PyTorch Data Visualization Problem Solving
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Aptitude Practice Questions Open Resource ↗
Helps you sharpen quantitative and logical reasoning skills essential for the initial screening test.
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Company Interview Preparation Guide Open Resource ↗
Provides insights into common interview patterns and technical questions asked by tech firms, useful for the technical round.
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Comprehensive Interview Prep Resources Open Resource ↗
Covers a wide range of topics from data structures to machine‑learning fundamentals, aiding overall interview readiness.
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Algorithm & Data Structure Problem Set Open Resource ↗
Offers practice problems to improve coding speed and accuracy, crucial for the technical coding assessment.

• Currently pursuing or recently graduated (within the last 12 months) with a B.Tech/M.Tech/B.Sc. in Computer Science, Computer Engineering, Information Technology, or a related technical discipline. • Minimum aggregate of 60% (or CGPA 6.0/10) in the qualifying degree. • No active backlogs at the time of application. • Batch year can be 2023, 2024, or 2025 (flexible for recent graduates). • Strong academic foundation in algorithms, data structures, and basic machine‑learning concepts. • Ability to work on‑site in Pune for the full internship duration.

1
Round 1: Online Aptitude & Logical Reasoning Test
2
Round 2: Technical Interview (coding & ML concepts)
3
Round 3: HR Interview
Amber is a fast‑growing technology startup headquartered in Pune, Maharashtra. Founded in 2018, the company focuses on building AI‑driven solutions for sectors such as healthcare, finance, and e‑commerce. With a team of over 150 engineers, data scientists, and product designers, Amber prides itself on a culture of rapid experimentation, collaborative problem‑solving, and continuous learning. The firm has recently secured Series A funding, which is being channelled into expanding its research labs and launching new AI products that aim to automate decision‑making and improve user experiences. The AI Engineering Intern role is designed for fresh talent eager to dive into real‑world artificial‑intelligence projects. Interns will work side‑by‑side with senior machine‑learning engineers, product managers, and data analysts to design, develop, and deploy models that power Amber’s flagship platforms. This is a full‑time, on‑site internship that offers hands‑on exposure to the end‑to‑end AI development lifecycle—from data ingestion and preprocessing to model training, evaluation, and production monitoring. Key Responsibilities: 1. Assist in collecting, cleaning, and preprocessing large datasets from diverse sources. 2. Develop and fine‑tune machine‑learning models using Python libraries such as scikit‑learn, TensorFlow, or PyTorch. 3. Write modular, well‑documented code and contribute to the company’s shared codebase on Git. 4. Participate in model evaluation, performance benchmarking, and error analysis. 5. Collaborate with product teams to translate business requirements into technical specifications. 6. Deploy prototypes to cloud environments (AWS/GCP) and monitor model drift. 7. Prepare technical reports and visualisations to communicate findings to non‑technical stakeholders. 8. Stay updated with the latest research papers and suggest innovative approaches for ongoing projects. 9. Support the team in building data pipelines and automation scripts. 10. Participate in code reviews and knowledge‑sharing sessions. Tech Stack: Python, Pandas, NumPy, scikit‑learn, TensorFlow/PyTorch, SQL, Git, Docker, AWS/GCP, Jupyter notebooks. Growth Path: Successful interns may be offered a full‑time Junior Machine‑Learning Engineer position, with clear progression to Senior Engineer, Lead AI Engineer, and eventually AI Product Manager roles. Amber encourages continuous upskilling through internal workshops, conference sponsorships, and mentorship programs. Why Join Amber? The internship provides a rare blend of startup agility and structured mentorship. Interns gain exposure to production‑grade AI systems, work on projects that impact real customers, and become part of a supportive community that values curiosity and impact. This experience can serve as a strong launchpad for a career in AI engineering.

Amber — Data Analytics & SQL Interview Guide

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

APTITUDE & LOGIC šŸ“–
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 ↗
COMPANY GUIDE šŸŽÆ
Amber Interview Preparation Corner

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

Open Resource ↗
MOCK TESTS & PAPERS šŸ“
Comprehensive Interview Prep Resources & Syllabus

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

Open Resource ↗
CODING PRACTICE šŸ’»
Algorithm and Data Structure Problem Set

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

Open Resource ↗
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, Machine Learning, Deep Learning, Data Preprocessing, SQL, Git, TensorFlow, PyTorch, Data Visualization, Problem Solving) & 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
Amber 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 ā–¼
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 ā–¼
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 ā–¼
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 ā–¼
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 ā–¼
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 Amber as a AI Engineering Intern?
Preparation Tip: Highlight Amber'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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