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- Tasks: Transform trading models into production-ready systems and build essential tooling.
- Company: Join Longshot Systems, a leader in sports betting analytics and trading.
- Benefits: Enjoy competitive salary, uncapped bonuses, private healthcare, and gym membership.
- Why this job: Make an impact in a dynamic field with cutting-edge machine learning technologies.
- Qualifications: Degree in a quantitative subject and strong software engineering skills required.
- 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’re hiring Machine Learning Engineers for our modelling engineering team. You’ll 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. The ideal candidate will have a strong software engineering background, with broad experience across a range of topics related to general high performance computing such as multi‑threading, networking, profiling and optimisation. Experience working with the NumPy/SciPy stack is essential, as is experience with tools like C++, Numba, etc. for performance optimisation. Knowledge of common ML algorithms and techniques is a plus, although not essential.
We are a hybrid working company, working Thursdays in our London (Farringdon) office and flexibly from home 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 (10:30‑5 pm) – 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
- Networking
Nice to Have
- 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
Benefits
- Participation in the uncapped company bonus scheme, typically 15‑25% of salary depending on experience
- 10% matched pension contributions
- Private healthcare insurance
- Long‑term illness insurance
- Gym membership
Senior Machine Learning Engineer employer: Longshot Systems
Contact Detail:
Longshot Systems Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Longshot Systems. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio or GitHub repo showcasing your projects, especially those involving Python and ML. This is your chance to demonstrate your engineering excellence and problem-solving abilities.
✨Tip Number 3
Ace the interview prep! Brush up on your coding skills and be ready for live coding challenges. Practise with pair programming scenarios to get comfortable with the format they use during interviews.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team at Longshot Systems.
We think you need these skills to ace Senior Machine Learning Engineer
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, C++, and any relevant ML libraries. We want to see how your skills match what we're looking for!
Show Off Your Projects: Include any personal or professional projects that showcase your software engineering skills and experience with high-performance computing. This is your chance to impress us with your hands-on work!
Craft a Compelling Cover Letter: Your cover letter should tell us why you're passionate about machine learning and how you can contribute to our team. Be genuine and let your personality shine through – we love to see enthusiasm!
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’s super easy!
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 and familiar with libraries like NumPy, SciPy, and Polars. Brush up on your coding skills, especially in C/C++, as you might be asked to demonstrate your proficiency during the technical interviews.
✨Prepare for Live Coding
Since there’s a live code review and pair programming session, practice coding under pressure. Use platforms like LeetCode or HackerRank to simulate the experience. Focus on writing clean, efficient code and explaining your thought process as you go.
✨Understand High Performance Computing
Get comfortable discussing multi-threading, profiling, and optimisation techniques. Be ready to share examples of how you've tackled performance issues in past projects, as this will show your analytical approach to problem-solving.
✨Show Your Passion for Engineering Excellence
During the interview, convey your pride in engineering best practices. Share experiences where you’ve encouraged others to maintain high standards. This will resonate well with their focus on quality and systematic approaches in software development.
