At a Glance
- Tasks: Transform trading models into production-ready systems and design innovative data engineering tools.
- Company: Join Longshot Systems, a leader in sports betting analytics and trading technology.
- Benefits: Enjoy uncapped bonuses, private healthcare, gym membership, and a matched pension scheme.
- Other info: Flexible hybrid working model with excellent career growth opportunities.
- Why this job: Make an impact in the exciting world of sports betting with cutting-edge machine learning.
- Qualifications: Strong software engineering skills, especially in Python and high-performance computing.
The predicted salary is between 48000 - 72000 £ per year.
At Longshot Systems we build advanced platforms for sports betting analytics and trading. We are 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.
Responsibilities
- Turn prototype trading models into production-ready systems in collaboration with the quantitative research teams.
- Design and build tooling, frameworks and data engineering to support strategy research and development.
- Architect the high-level design of strategy software to minimise trading latency and enable scaling.
- Contribute to a Python-based ML stack using modern libraries and tooling (e.g., Polars, Ray, Plotly).
Qualifications
- Strong software engineering background with broad experience in high performance computing (multi-threading, networking, profiling, optimisation).
- Essential experience with NumPy/SciPy stack; experience with C++, Numba or similar performance-optimisation tools is a plus.
- Knowledge of common ML algorithms and techniques is a plus but not essential.
Working arrangement
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) - 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, 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
- Experience with Python programming
- Proficient in C/C++ on modern architectures
- Experience with the NumPy/SciPy 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
Nice to have
- Data engineering experience in Python (e.g., Dagster, Prefect)
- Experience optimising dataframe code in Pandas or Polars
- Experience with machine learning techniques and libraries/frameworks (scikit-learn, PyTorch, TensorFlow)
- Experience in scientific computing with other languages and frameworks
Benefits
- Participation in the uncapped company bonus scheme
- 10% matched pension contributions
- Private healthcare insurance
- Long term illness insurance
- Gym membership
Senior Machine Learning Engineer in London employer: Longshot Systems
Longshot Systems is an exceptional employer for those passionate about machine learning and sports analytics, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from opportunities for professional growth through hands-on experience with cutting-edge technologies like Docker, Kubernetes, and cloud platforms, all while contributing to impactful projects in the fast-paced world of sports betting. Located in a vibrant tech hub, the company provides a stimulating environment where creativity and technical expertise thrive.
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