Senior Quantitative Engineer, Systematic Cross Commodity

Millennium; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Millennium seeks a Senior Quantitative Engineer to advance its trading infrastructure in London. You will build and maintain research tools and production systems for alpha discovery, signal processing and trade execution, leveraging Python, C++, and modern distributed platforms.

The role emphasizes real-time data ingestion, scalable compute, and robust software design within a small, collaborative team. A strong CS or engineering background and 5+ years in the field are preferred.

Qualifications

• 5+ years of experience in distributed systems and quantitative engineering.
• Proficiency in Python and C++ and modern data tools.
• Familiarity with Docker, Kubernetes, Ceph, MongoDB and Kafka.
• Strong fundamentals in numerical computing, data structures and algorithms.
• Experience with CICD and large codebases.

Responsibilities

• Develop sophisticated research tooling to enable and accelerate alpha discovery.
• Develop real-time event-driven systems for signal computation, trade-decision-making and execution.
• Design, implement, and maintain core systems and services for real-time data ingestion, retrieval and distributed compute for research and production.
• Oversee the operation of all components to ensure resilience and detect defects as they arise.

Skills

Python

C++

Distributed systems

Numpy

Polars

Scikit-learn

PyTorch

Docker

Kubernetes

Ceph

MongoDB

Kafka

Version control

Testing frameworks

CI/CD

Build systems

Communication

Problem-solving

Analytical skills

Education

Master's or PhD in Computer Science, Physics, Engineering, Statistics, Applied Mathematics

Tools

Git

Job description

Senior Quantitative Engineer, Systematic Cross Commodity

We are a small, collaborative systematic trading team based in London looking for a senior engineer to aid in the implementation and continued development of our team's core software and technical infrastructure. The role involves the development and maintenance of sophisticated tools for alpha research along with the production systems used in feature engineering, portfolio construction, and trade execution. The ideal candidate should be an expert engineer with a deep theoretical foundation, extensive systems design experience, and significant expertise in both high-level and systems programming languages (we primarily use Python and C++) and should be motivated by the idea of playing a pivotal part in a high-impact, technology-driven business. Besides strong technical skills, we value exceptional attention to detail, a strong intuition for the pragmatism-robustness tradeoff and, most importantly, someone who works well in a close-knit, start-up-style team.

Location

London

Principal Responsibilities

• Develop sophisticated research tooling to enable and accelerate alpha discovery.


• Develop real-time event-driven systems for signal computation, trade-decision-making and execution.


• Design, implement, and maintain the core systems and services to enable real time data ingestion, retrieval and distributed compute for both research and production.


• Oversee the ongoing operation of all components within the systems landscape to ensure resilience and detect defects as they arise.

Preferred Technical Skills

• Exceptional programming skills in both high-level and low-level languages (Python & C++ or similar).


• Familiarity with modern distributed computing platforms (specifically: docker, kubernetes, ceph, mongodb & kafka).


• Theoretical proficiency in numerical computing, online algorithms, data structures, networking, databases, and operating systems.


• Familiarity with typical quantitative research toolchains including Numpy, Polars, Scikitlearn, Pytorch, etc.


• DevOps: version control, testing frameworks, release processes, build systems.


• Excellent communication, problem-solving, and analytical skills.

Preferred Experience

• Extremely strong computer science or engineering background with 5+ years of experience.


• Experience designing and implementing: Distributed Systems.


• Real-time event-driven systems.


• Large-scale time series data ingress, storage and processing.


• Experience with the architectural design of large-scale software systems.


• Experience with systematic futures trading.


• Exposure to CICD-style implementation/release methodologies with a large complex codebase.


• Master’s or PhD in Computer Science, Physics, Engineering, Statistics, Applied Mathematics, or related technical field.

Additional Relevant Experience

• Prior role as a quantitative developer supporting a multi-asset systematic trading business.


• Experience with a broad spectrum of finance-relevant data sources (e.g. tick data, fundamental data and alternative data).


• Functional understanding of foundational trading & risk management concepts.

Target Start Date

• As soon as possible