Software Engineer – AI Agents & Machine Learning Infrastructure

Description

We are partnering with a market-leading quantitative trading firm to hire a Software Engineer focused on building advanced AI agents and scalable machine learning infrastructure. This role sits at the intersection of low-latency systems, applied AI, and high-performance computing, supporting research and production trading environments.

Key Responsibilities

  • Design and develop AI agent systems to support automated decision-making, research workflows, and trading strategy augmentation.

  • Build and maintain robust machine learning frameworks used for model training, evaluation, and deployment at scale.

  • Collaborate closely with quantitative researchers and traders to translate research ideas into production-grade systems.

  • Optimize infrastructure for performance, scalability, and low-latency execution in a live trading environment.

  • Develop tooling for experiment tracking, feature engineering, and model lifecycle management.

  • Contribute to the integration of LLMs and reinforcement learning approaches into trading and research workflows.

  • Ensure high standards of code quality, testing, and system reliability.

Required Skills

  • Strong software engineering fundamentals with proficiency in Python and/or C++.

  • Experience building machine learning systems or infrastructure (training pipelines, distributed systems, or model serving).

  • Solid understanding of machine learning concepts (supervised/unsupervised learning, reinforcement learning, or deep learning).

  • Familiarity with modern ML frameworks such as PyTorch, TensorFlow, JAX, or similar.

  • Experience working in Linux environments and with performance-critical systems.

  • Strong problem-solving skills and ability to work in a fast-paced, research-driven environment.

Preferred Qualifications

  • Exposure to AI agents, LLM-based systems, or autonomous decision-making frameworks.

  • Experience in quantitative finance, trading systems, or time-series modelling.

  • Knowledge of distributed computing, Kubernetes, or GPU acceleration.

  • Familiarity with low-latency system design or high-performance computing environments.

Apply Today

Thank you for your interest in this opportunity. Please complete the form below and upload any relevant documents. A member of our team will review your application and be in touch soon.

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