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- Tasks: Transform trading models into production-ready systems and design high-performance software.
- Company: Join Longshot Systems, a leader in sports betting analytics and trading.
- Benefits: Enjoy competitive salary, private healthcare, gym membership, and a bonus scheme.
- Why this job: Be at the forefront of machine learning in a dynamic and innovative environment.
- Qualifications: Strong Python skills, experience with NumPy/SciPy, and a degree in a quantitative field.
- Other info: Flexible hybrid working 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'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. 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 & techniques is a plus, although not essential.
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
A degree in a quantitative, technical subject (e.g. Machine Learning, Maths, Physics) from a top university is required. Significant software engineering skills and experience, especially on the modern Python ML stack, are essential. The candidate should take pride in engineering excellence and encourage best practice in others, with 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
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, and gym membership are also included.
Senior Machine Learning Engineer in London employer: Longshot Systems Ltd
Contact Detail:
Longshot Systems Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Longshot Systems. A friendly chat can sometimes lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Prepare for those technical interviews! Brush up on your Python skills and be ready to showcase your knowledge of the NumPy/SciPy stack. Practising live coding can really help you feel more confident.
✨Tip Number 3
Showcase your projects! If you've worked on any cool machine learning models or performance optimisation tasks, make sure to highlight them during your interviews. Real-world examples can set you apart from the crowd.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
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, C++, and any relevant ML libraries. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include any projects that demonstrate your software engineering skills and experience with high-performance computing. If you've worked on trading models or similar systems, make sure to mention them. We love seeing real-world applications of your work!
Craft a Compelling Cover Letter: Your cover letter should reflect your passion for machine learning and sports analytics. Tell us why you're excited about this role at Longshot Systems and how you can contribute to our team. Be genuine and let your personality shine through!
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 it gets into the right hands. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at Longshot Systems Ltd
✨Know Your Tech Stack
Make sure you’re well-versed in the Python ML stack, especially libraries like NumPy and SciPy. Brush up on your knowledge of performance optimisation tools like C++ and Numba, as these will likely come up during technical discussions.
✨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 and get comfortable with explaining your thought process while coding.
✨Understand the Business Context
Familiarise yourself with sports betting analytics and trading. Knowing how your role as a Machine Learning Engineer fits into the bigger picture will help you answer questions more effectively and show your genuine interest in the company’s mission.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the tech stack, and the challenges they face. This not only shows your enthusiasm but also helps you gauge if the company culture aligns with your values.