Longshot Systems Tech Stack

Low-latency trading software for sports betting markets

Software Development London, England 11–50 employees Founded 2016 Privately Held

Longshot Systems builds high-throughput, low-latency trading systems for sports betting — processing thousands of signals per second with constraints similar to high-frequency trading shops. The stack is heavily quantitative (Python, NumPy, SciPy, PyTorch, TensorFlow, Polars, Ray) paired with systems languages (C++, Rust, Go) and orchestration tools (Dagster, Prefect), reflecting an engineering org optimizing for both model iteration and production stability. Hiring is senior-weighted and concentrated in engineering and research, signaling active work on model improvement and infrastructure scaling rather than sales expansion.

Tech Stack 22 technologies

Core StackPython NumPy C++ Dagster Prefect Pandas scikit-learn PyTorch TensorFlow AWS Linux Go Rust Java C# Ansible Kaggle Polars Ray Plotly SciPy Numba

What Longshot Systems Is Building

◆Challenges

Improving predictive power of models
Infrastructure evolution
Automation and repeatability
Performance and stability issues
Minimising trading latency
Scaling strategy software
Turning prototype models into production
Strict latency requirements
High throughput requirement
Reducing latency in trading

▲Active Projects

Develop new machine learning models
Improve existing state-of-the-art solutions
Integrating more trading venues
Maintaining historical data repository
Infrastructure evolution
Automation and repeatability
Productionizing prototype trading models
Building tooling for strategy research
Architecting strategy software design
Optimising key parts of the platform

Hiring Activity

Accelerating10 roles · 5 in 30d

Department

Engineering

Data

Research

Seniority

Senior

Junior

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About Longshot Systems

Longshot Systems is a London-based startup founded in 2016 that develops trading software and tools for sports betting markets. The company's core product suite handles real-time decision-making under strict latency and throughput constraints — thousands of trading signals per second must be evaluated and acted upon with minimal delay. The team operates across engineering, data, and research functions, building machine learning models, maintaining historical data infrastructure, and integrating new trading venues. Active work spans model productionization, latency optimization, and platform scaling.

HeadquartersLondon, England

Company Size11–50 employees

Founded2016

Hiring MarketsUnited Kingdom

Frequently Asked Questions

What tech stack does Longshot Systems use?

Python, NumPy, SciPy, PyTorch, TensorFlow, Polars, Ray, C++, Rust, Go, Dagster, Prefect, and AWS. Stack emphasizes numerical computing and systems performance for real-time trading.

What is Longshot Systems working on?

Developing new ML models, productionizing prototypes into production systems, integrating additional trading venues, optimizing latency and throughput, and evolving infrastructure for automation and repeatability.