ML/AI Quant Intern

0 years

0 Lacs

Posted:1 month ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

Company Description AlgoEdge is a quantitative research firm that provides innovative trading solutions to investment managers such as hedge funds and family offices. Our proprietary strategies cover multiple asset classes and are designed to be market-neutral. We emphasize innovation and precision, rigorously back-testing and live testing our strategies to ensure optimal performance. ML/AI Quant Internships at AlgoEdge – Gurgaon Office Are you passionate about Machine Learning, AI, and Financial Markets ? Do you want to build real trading strategies , not just theoretical models? At AlgoEdge , we're building India's next-gen quant trading and analytics platform , leveraging multi-factor models, AI, and big data to outperform global markets. 👉 We’re currently hiring 2 interns / junior quant researchers to join our core team at Gurgaon. 🔬 What You'll Work On: ✔ Build predictive ML models for alpha generation ✔ Enhance execution logic using reinforcement learning & NLP ✔ Backtest strategies using large-scale tick and alt-data ✔ Work closely with experienced quants and traders in a collaborative, high-impact environment 🎓 Who Should Apply: BTech/MSc/PhD candidates from top institutes (IITs, BITS, ISI, etc.) or equivalent research experience Strong skills in Python, NumPy/pandas, TensorFlow/PyTorch Background in Statistics, Mathematics, Computer Science, or Engineering Curiosity for markets and a passion for solving complex problems with data Strong team spirit and a willingness to learn in a fast-paced, startup environment ✨ Why AlgoEdge? ✅ Paid internship with industry-best compensation ✅ Potential fast-track to full-time role ✅ Learn from seasoned quants ✅ Flat structure with daily exposure to real trading decisions ✅ Work on actual strategies deployed in live markets 📍 Location: Gurgaon Apply: https: docs.google.com/forms/d/1FEZgxujENiY_sO9CrmX2T52QxeISVZsbGw61DL3Mk-A/edit Show more Show less

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