We are looking for Quantitative Backend Developer (C++) to join our engineering team and help us to improve the performance of our existing backtesting platform and assist us in real-time trading implementation

Every day our algorithms process more than 500 million data points. As a result, low latency and fault tolerance are essential for us.

- Improve the performance and speed of our back-testing and simulation frameworks.
- Real-time implementation of systematic strategies and signals.
- Collaborate with quantitative researchers to provide full-technical support for latency-sensitive HFT strategy automation.
- Develop low-latency code using the latest C++ standards.

- Bachelor’s degree in Computer Science or Computer Engineering or related field.
- Exceptional knowledge of algorithms and data structures.
- Strong computer science fundamentals and in-depth knowledge and experience in developing high-performance, low-latency code in C++ (Linux).
- Proficiency in Python.
- Experience in profiling, optimizing latency and throughput.
- Experience working with pybind11.
- Experience in the development of Linux systems.
- Understanding the principles of OOP, design patterns
- Expert knowledge of SQL and columnar databases.
- Experience working with streaming data, async, and parallel processing.

Desirable skills:
- Experience with message brokers: Apache Kafka/Redpanda.
- Experience with Docker and Kubernetes.
- Financial/Trading applications development experience.

About Machine Factor Technologies

Machine Factor Technologies is a London-based algorithmic trading digital assets fund. Our trading strategies operate on centralised and decentralised crypto markets, trading futures and options instruments.
We believe that a systematic, data‑driven approach is a key to deliver extraordinary investment performance. Our goal is to bring uncorrelated, absolute returns to our clients by applying various techniques in statistical arbitrage, volatility and high-frequency trading (HFT).

Company website:

DOU company page:

Job posted on 23 June 2022
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