Senior Machine Learning Engineer

Company

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

We’re hiring Machine Learning Engineers for our modelling engineering team. You would 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.

• Work closely with quantitative research teams to convert prototype trading models into production‑ready systems.
• Design and build the tooling, frameworks and data engineering required to support strategy research and development.
• Architect the high‑level design of strategy software to minimise trading latency and scale effectively.

• 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 (10:30‑5 pm) – a one‑day programming exercise designed to be similar to the real work we do in the team

• A degree in a quantitative, technical subject (e.g. Machine Learning, Maths, Physics) from a top university
• Significant software engineering skills and experience, especially on the modern Python ML stack
• Takes pride in engineering excellence and encourages best practice in others
• A systematic, analytical approach to tackling problems and designing solutions

• Python programming
• Proficient in C/C++ on modern architectures
• Experience with the Num Py/Sci Py stack
• Working with Linux platforms with knowledge of various scripting languages
• Strong general high performance computing:
• Multi‑threading
• Profiling Python/C/C++ and performance optimisation
• Networking

• Data engineering experience in Python, e.g. with libraries like Dagster, Prefect etc.
• Experience optimising 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 in scientific computing with other languages & frameworks.

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

Mid‑Senior level

Full‑time

London (Farringdon) office; hybrid – Thursdays in office, flexible rest of the week

10 am to 6 pm UK time, Monday – Friday (supports flexible working)