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- 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.
- 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.
- Other info: Flexible hybrid working model with excellent career growth opportunities.
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
Contact Detail:
Longshot Systems Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at Longshot Systems. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back! Share your projects, especially those involving Python and ML tools like Polars or Ray. Let them see what you can do in action!
✨Ace the Technical Interviews
Prepare for those coding challenges by practising live coding and pair programming. Brush up on your Python skills and be ready to discuss your thought process. Remember, it’s not just about getting the right answer but how you approach the problem!
✨Apply Through Our Website
Don’t forget to apply directly through our website! It shows you're genuinely interested and makes it easier for us to find your application. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with Python, NumPy/SciPy, and any relevant projects that showcase your skills in high-performance computing and machine learning.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about sports betting analytics and how your background aligns with our needs. Be sure to mention any experience with modern ML libraries like Polars or Ray.
Showcase Your Projects: If you've worked on any relevant projects, whether personal or professional, make sure to include them. We love seeing practical applications of your skills, especially if they relate to trading models or performance optimisation.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Longshot Systems
✨Know Your Tech Stack
Make sure you’re well-versed in the Python ML stack mentioned in the job description. Brush up on libraries like NumPy, SciPy, and any others listed, such as Polars and Ray. Being able to discuss your experience with these tools will show that you're ready to hit the ground running.
✨Prepare for Live Coding
Since there's a live code review and pair programming involved, practice coding under pressure. Use platforms like LeetCode or HackerRank to simulate the experience. Focus on writing clean, efficient code and be prepared to explain your thought process as you go.
✨Understand the Business Context
Familiarise yourself with sports betting analytics and trading. Understanding how machine learning can optimise trading strategies will help you connect your technical skills to the company's goals. This knowledge can set you apart from other candidates.
✨Showcase Your Problem-Solving Skills
During the interviews, be ready to demonstrate your systematic and analytical approach to problem-solving. Prepare examples from your past work where you tackled complex issues, especially in high-performance computing or multi-threading scenarios. This will highlight your engineering excellence.
