At Longshot Systems we build advanced platforms for sports betting analytics and trading.

We're hiring a Senior Machine Learning Engineer for our modelling engineering team. You'd be working closely with the quantitative research teams to turn prototype trading models into production-ready systems, design and build the tooling, frameworks and data engineering required to support strategy research and development as well as architecting the high-level design of the strategy software to minimise trading latency and scale effectively. Our ML stack is Python based and utilises modern ML libraries and tooling including Polars, Ray, Plotly etc.

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.

Our interview process is as follows:

• Intro call (30 mins) - your background + interests
• 1st Technical interview (30 mins) - live code review & pair programming
• 2nd Technical interview (60 mins) - deep dive technical questions
• Full assessment day (10:30–5pm) - a one day programming exercise designed to be similar to the real work we do in the team

Requirements

• A degree in a quantitative or technical subject from a top university
• Significant software engineering experience, especially on the modern Python ML stack
• Eligible to work in the UK

Experience with:

• Python programming
• Experience with the NumPy/SciPy stack
• Experience working with Linux platforms and scripting languages
• Experience with high-performance computing, including:
• Multithreading
• Profiling Python/C/C++ and performance optimisation
• Networking

Nice to have:

• Proficiency in C or C++ on modern architectures
• Data engineering experience in Python, e.g. with libraries like Dagster or Prefect
• Experience optimising dataframe code, e.g. in Pandas or ideally Polars
• Experience with machine learning techniques and related libraries and frameworks e.g. scikit-learn, PyTorch, TensorFlow etc
• Experience in scientific computing with other languages & frameworks

Benefits

• Participation in the uncapped company bonus scheme
• 10% matched pension contributions
• Private healthcare insurance
• Long term illness insurance
• Gym membership