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- Tasks: Transform trading models into production-ready systems and build innovative tools.
- Company: Join Longshot Systems, a leader in sports betting analytics.
- Benefits: Enjoy competitive salary, bonuses, private healthcare, and gym membership.
- Why this job: Make an impact in a dynamic field with cutting-edge technology.
- Qualifications: Strong Python skills and experience in high-performance computing 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 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. 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 is 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 offered.
Senior Machine Learning Engineer 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
✨Tip Number 1
Get your networking game on! Connect with folks in the industry, especially those at Longshot Systems. LinkedIn is a great place to start – drop them a message, share your passion for machine learning, and let them know you're keen to join the team.
✨Tip Number 2
Prepare for those technical interviews like a pro! Brush up on your Python skills and get comfy with live coding. Practise pair programming with a friend or use platforms like LeetCode to sharpen your problem-solving skills.
✨Tip Number 3
Showcase your projects! If you've worked on any cool machine learning models or optimised systems, make sure to highlight them during your interviews. Having real-world examples can really 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, it shows you're genuinely interested in being part of the Longshot Systems family.
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 align with our needs!
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, let us know! We love seeing real-world applications.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for easy reading and make sure to highlight your key achievements. We appreciate straightforward communication!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to hear from you!
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 techniques using C++ and Numba, as these will likely come up during technical interviews.
✨Practice Live Coding
Since the first technical interview involves live code review and pair programming, practice coding in real-time. Use platforms like LeetCode or HackerRank to simulate the experience and get comfortable with explaining your thought process as you code.
✨Understand High Performance Computing
Familiarise yourself with concepts related to multi-threading, networking, and profiling. Be prepared to discuss how you’ve tackled performance issues in past projects, as this is crucial for the role.
✨Prepare for the Full Assessment Day
The full assessment day will mimic real work scenarios, so practice coding exercises that involve building production-ready systems. Focus on designing solutions that minimise latency and scale effectively, as this aligns with what Longshot Systems is looking for.
