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REQUIREMENT_ID_70 • 3-DAY_ACTIVE_POLICY

Intern - AI/ML

Company
Company Tower Research Capital
Type
Opportunity Type Internship
Salary
Stipend / Salary Stipend: Rs 25,000 per month
Location
Location Gurgaon, India
Posted Date
Posted Date Today
Python Linux SQL Git Bash scripting TensorFlow PyTorch MLOps Agentic AI tooling Claude Code Model Context Protocol MCP statistical modeling machine learning low‑latency programming
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Aptitude and Logical Reasoning Practice Open Resource ↗
Helps sharpen analytical thinking and problem‑solving skills essential for coding and ML interviews.
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Interview Preparation and Mock Sessions Open Resource ↗
Provides structured interview questions and mock interview practice for technical and behavioral rounds.
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Coding Practice and Algorithmic Challenges Open Resource ↗
Offers a wide range of coding problems to improve algorithmic proficiency and coding speed.
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Data Structures and Algorithms Problems Open Resource ↗
A comprehensive set of problems to master data structures, algorithms, and problem‑solving techniques.

Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, Data Science, or related field from a top university. Minimum 70% (or 7.0 CGPA) in the final year or equivalent. No backlogs allowed. Availability to join an in‑office internship for six months starting January 2027.

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Round 1: Technical interview covering coding, ML concepts, and agentic AI fundamentals
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Round 2: System design and MLOps discussion with senior engineers
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Round 3: HR and cultural fit interview
Tower Research Capital is a leading global quantitative trading firm that blends cutting‑edge technology with sophisticated financial strategies. With a presence in major financial hubs worldwide, the company leverages high‑frequency trading, statistical arbitrage, and systematic research to generate alpha for its clients. Tower’s culture is built on collaboration, intellectual curiosity, and a relentless pursuit of excellence, allowing engineers and analysts to experiment, iterate, and learn in a fast‑paced environment. The Intern – AI/ML role is designed for students who are passionate about artificial intelligence, machine learning, and agentic systems. Interns will work closely with senior data scientists and software engineers to build and evaluate multi‑agent frameworks that power trading strategies. The internship spans six months, starting January 2027, and requires on‑site presence in Gurgaon. Key responsibilities include: 1. Designing and implementing multi‑agent systems, orchestrating agents, and integrating with protocols such as Model Context Protocol (MCP). 2. Developing agentic coding tools (e.g., Claude Code) to accelerate development and automate workflows. 3. Building and training machine learning models using TensorFlow, PyTorch, or equivalent frameworks. 4. Deploying models to production with MLOps practices, monitoring performance, and maintaining model lifecycle. 5. Conducting experiments to evaluate model performance and fine‑tuning hyperparameters. 6. Collaborating with trading and engineering teams to translate business requirements into technical solutions. 7. Writing clean, well‑documented Python code and maintaining version control with Git. 8. Using Linux, SQL, and Bash scripting for data extraction, preprocessing, and deployment. 9. Participating in code reviews, knowledge sharing sessions, and continuous learning workshops. 10. Contributing to the company’s open‑source projects and internal tooling. Tech stack: Python, TensorFlow/PyTorch, Linux, SQL, Git, Bash, MLOps tools (MLflow, Kubeflow), agentic AI frameworks, Claude Code, MCP. Growth path: Interns who demonstrate strong technical acumen and cultural fit may be offered full‑time roles as Data Scientists, ML Engineers, or Research Scientists. The company provides mentorship, access to global conferences, and a clear promotion ladder. Why join Tower? The firm offers a collaborative environment where ideas are valued over ego, generous paid time off, wellness benefits, and a culture that rewards performance while maintaining work‑life balance. The internship provides hands‑on experience with real‑world trading systems, exposure to high‑frequency data, and the opportunity to work alongside world‑class engineers.

Tower Research Capital — 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.

Open Resource ↗
COMPANY GUIDE 🎯
Tower Research Capital Interview Preparation Corner

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

Open Resource ↗
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.

Open Resource ↗
CODING PRACTICE 💻
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, Linux, SQL, Git, Bash scripting, TensorFlow, PyTorch, MLOps, Agentic AI tooling, Claude Code, Model Context Protocol, MCP, statistical modeling, machine learning, low‑latency programming) & 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
Tower Research Capital 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 Tower Research Capital as a Intern - AI/ML?
Preparation Tip: Highlight Tower Research Capital'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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