Core Engineering Team

Company Description : Redstocks Technology LLP is a Quant-as-a-Service (QaaS) platform that supports mid-tier brokers in India by providing sophisticated trading algorithms. Our platform offers optimization tools for risk management, personalized trade recommendations, and portfolio adjustments as a customizable, white-labeled solution. By continually collecting trade data, equity holdings, and market behavior patterns, we enhance the accuracy and effectiveness of our algorithms over time. This creates a self-improving feedback loop that sets us apart. Our revenue model includes licensing our technology and taking a cut of the trades executed through our system, positioning us as the tech backbone for the next generation of data-driven broking. Role Description : We are inviting applications from undergraduate students (1st to final year) with serious interest in: Quantitative Modeling & Algorithmic Trading Backend/Infra Engineering (APIs, real-time systems) Machine Learning (prediction, signal enhancement) Systems Architecture & Deployment Overview : Commitment : 10–15 hours/week Mode : Remote / Hybrid Duration : 6 months minimum Incentive : ESOPs granted after 6 months based on contribution and intent to stay Work With : Founders and core contributors, directly impacting product and pilot rollouts This is a high-responsibility, high-reward opportunity for students who want to build real systems not side projects and help shape the future of India's trading ecosystem. Minimum Qualifications : Currently pursuing a B.Tech / B.Sc / Integrated Program in Computer Science, Mathematics, Data Science, Engineering, or related fields (1st to Final year). Strong understanding of at least one programming language (Python, C++, Rust, or Go preferred). Familiarity with Git/GitHub , version control workflows, and collaborative development. Ability to dedicate 10–15 hours per week consistently for 6 months. Willingness to learn independently and contribute to production-grade systems. Preferred (Bonus) Qualifications : Prior experience in backend development , APIs , or working with Docker/Kubernetes . Exposure to algorithmic trading , quant research , or financial systems (even as hobby projects). Hands-on with ML frameworks (e.g., PyTorch, TensorFlow, or Scikit-learn) or backtesting libraries. Familiarity with low-latency architecture or high-frequency data handling. Strong written documentation habits, or experience contributing to open-source projects. Who should apply ? Students who’ve built side projects , won hackathons , or contributed to live systems. Those looking for deep, real-world engineering experience and not just resume lines. People who care about building something that can scale across India's fintech landscape.

Created: 2025-07-07