AI/ML Research Intern – Quantitative Trading & Financial Machine Learning (Remote)

Internship Overview

This 6-month research internship offers in-depth exposure to developing AI and machine learning models tailored for quantitative trading and financial market analysis. Interns will engage in hands-on tasks involving historical and intraday stock market data processing, modeling, evaluation, and deployment within a financial technology context.

Key Responsibilities

• Conduct research and development on AI/ML algorithms focused on quantitative trading strategies and market insights.
• Process and analyze time-series financial data using Python libraries such as Pandas and NumPy.
• Design, train, test, and optimize machine learning models leveraging algorithms like XGBoost, LightGBM, and Random Forest.
• Engineer features using multiple data points including price, volume, volatility, technical indicators, and market context.
• Implement time-series validation protocols including walk-forward testing, backtesting, and safeguards against data leakage and overfitting.
• Assess model performance using diverse metrics: accuracy, precision, Sharpe ratio, profit factors, drawdowns, and returns per trade.
• Investigate integration of external information such as news and market sentiment for enhanced model inputs.
• Support development of AI-based trading signals covering risk assessment, probability confidence, entry/exit points, and trade management decisions.
• Assist with building or integrating RESTful APIs via FastAPI to connect machine learning models with backend and user interface components.
• Maintain version-controlled, reusable, and well-documented codebases using Git and GitHub.
• Explore new methodologies, compare models objectively, and iteratively refine the machine learning pipeline.
• Collaborate closely with the company founder and existing development team to advance the MVP of an AI-driven trading analytics platform.

Candidate Profile and Eligibility

• Applicants must be available to work remotely and start between August 10, 2026, and September 14, 2026, for a full 6-month duration.
• Open to final year students and recent graduates (0–1 year experience) holding degrees in Computer Science, AI, Data Science, Mathematics, Statistics, or related disciplines (B.Tech/B.E./M.Tech/MCA/M.Sc).
• Preference for candidates with backgrounds from reputed institutes such as IITs, IIITs, NITs, or government/state engineering colleges though institute name is not mandatory.
• Strong proficiency in Python, Pandas, NumPy, and scikit-learn is essential.
• Experience with machine learning techniques like XGBoost and LightGBM, and familiarity with financial datasets, time-series modeling, or quantitative trading is highly desirable.
• Understanding of crucial ML concepts such as overfitting, data leakage, and appropriate dataset partitioning for training, validation, and testing is necessary.
• Knowledge of FastAPI, Git/GitHub workflows, and SQL is advantageous.
• Excellent problem-solving skills, a motivated approach to research, and self-directed learning qualities are expected.
• A keen interest in stock markets, quantitative trading, financial machine learning, or broader FinTech domains is strongly favored.
• Applicants should be prepared to clearly describe and implement their machine learning strategies during technical evaluations.
• The company encourages women seeking to start or restart their careers to apply.

Compensation and Benefits

• Monthly stipend ranging from INR 12,000 to 15,000.
• Certificate of internship completion upon successful conclusion.
• Flexible working hours supporting remote engagement.

About the Company

JPSP Technologies is a software firm specializing in a variety of IT services, including software and web development, mobile applications, AI solutions, and HR consulting.