AI/ML

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

• A bachelor’s, master’s, or PhD degree (ongoing or completed), or equivalent qualification, from a top university, with availability to join an in-office internship for six months starting January 2027.
• Expertise in modern agentic AI tooling is required, including agentic coding assistants such as Claude Code (or similar), building multi-agent systems, and integrating with protocols and frameworks such as Model Context Protocol (MCP) or agent skills.
• Experience training, building, and deploying machine learning models using TensorFlow, PyTorch, or similar frameworks.
• Familiarity with MLOps practices for model deployment, productionization, and lifecycle management.