Intern - AI/ML

Tower Research Capital is recruiting for Intern - AI/ML in gurgaon. This listing was last seen on the firm's own job board on August 22, 2026.

A federation of independent high-frequency teams, so the hiring bar and the culture vary by desk.

What sets Tower Research Capital apart: Independent trading teams with their own hiring standards. Latency engineering weighted heavily across most desks. Large India presence through its Gurgaon office.

Related preparation: Quantitative Researcher (QR) Career Roadmap, Machine Learning Quant Career Roadmap, Quant Strategist (Desk Quant) Career Roadmap, Quant Data Scientist (Alternative Data) Roadmap, Quant Research Ops (MLOps) Roadmap and Financial Data Scientist Career Roadmap.

The role, as Tower Research Capital describes it, published on August 20, 2026 and reproduced from their job board:

Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.

Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.

At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.

At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.

Responsibilities

Building and evaluating multi-agent systems, including agent orchestration, tool-calling, and integration with protocols and frameworks such as Model Context Protocol (MCP) and agent skills.

Implementing agentic coding tools, such as Claude Code, to accelerate development, automate workflows, and build internal tooling.

Developing and implementing statistical and machine learning algorithms and models to support business and technical requirements.

Contributing to MLOps practices for deploying, monitoring, and maintaining machine learning models in production environments.

Analyzing model performance through experiments and testing, while contributing to the optimization and fine-tuning of existing models.

Qualifications