Longshot Systems Ltd
Senior Machine Learning Engineer (Python / C++)
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About Longshot Systems
At Longshot Systems we build advanced platforms for sports betting analytics and trading.
About the Role
We're hiring Machine Learning Engineers across our core ML engineering and horse racing teams. You'd be designing, building, and productionising ML pipelines, tooling, visualisation, frameworks, and data engineering workflows to support strategy research, analysis, and development, working closely with our quantitative research teams to turn prototype trading models into production-ready systems. You'd also help shape the high-level architecture of our strategy software so it scales effectively and keeps trading latency low. We operate a hybrid Python/C++ engineering stack. A large portion of our stack is Python-based (utilising libraries like NumPy, SciPy, PyTorch, Polars, Ray, Plotly, and Dash), but an increasing amount of our most performance-critical systems are written in modern C++ (C++23). We are actively looking to expand our team's C++ expertise to drive these low-latency components forward.
Key Responsibilities
- Design, build, and productionise ML pipelines, tooling, visualisation, frameworks, and data engineering workflows.
- Work closely with quantitative research teams to turn prototype trading models into production-ready systems.
- Help shape the high-level architecture of our strategy software to ensure scalability and low latency.
- Write clean, maintainable Python code and optimize performance-critical architecture with C++.
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Requirements
- A degree in a quantitative, technical subject (e.g., Machine Learning, Maths, Physics, Computer Science) from a top university.
- Strong software engineering background in Python alongside solid expertise in modern C++ (C++23).
- Experience building, optimizing, and integrating low-latency performance-critical components in a hybrid Python/C++ environment.
- Strong experience designing and maintaining ML pipelines and data engineering workflows.
- Familiarity with modern engineering practices such as CI/CD, containerisation (e.g., Docker, Kubernetes), and automated testing.
- Experience with cloud platforms (e.g., AWS, GCP, or Azure).
- Comfortable working in a Linux environment.
Nice to Have
- Advanced data engineering experience in Python, e.g., with libraries like Dagster, Prefect, etc.
- Experience optimizing dataframe code, e.g., in Pandas or ideally Polars.
- Experience of machine learning techniques and related libraries and frameworks, e.g., scikit-learn, PyTorch, Tensorflow, etc.
- Experience deploying and serving ML models in production, including model monitoring and real-time inference.
- Experience in scientific computing with other languages & frameworks.
- Strong general high-performance computing (multi-threading, networking, profiling, and optimisation).
- Familiarity with Python data science tools and frameworks (e.g., NumPy, PyTorch, Polars).
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Benefits
- Participation in the company bonus scheme.
- 10% matched pension contributions.
- Private healthcare insurance.
- Long-term illness insurance.
- Gym membership.
Work Schedule
We are a hybrid working company, working Thursdays in our London (Farringdon) office and flexible the rest of the week. Our typical working hours are 10 am to 6 pm UK time, Monday to Friday, but we support flexible working and trust our team to manage their own schedules to meet their goals.
Interview Process
- Intro call (30 mins) - Learn more about your background and discuss the role.
- Technical interview - Python & C++ software engineering assessment.
- Full assessment day (10:00–5pm) - A one-day programming exercise designed to be similar to the real work we do in the team.
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