At a Glance
- Tasks: Design and build advanced ML pipelines for sports betting analytics.
- Company: Join Longshot Systems, a leader in sports betting technology.
- Benefits: Enjoy a competitive salary, private healthcare, gym membership, and a bonus scheme.
- Other info: Hybrid work model with excellent career growth opportunities.
- Why this job: Make an impact in a dynamic environment with cutting-edge tech and flexible working.
- Qualifications: Strong Python and C++ skills, experience in ML pipelines, and data engineering.
The predicted salary is between 72000 - 88000 £ per year.
At Longshot Systems we build advanced platforms for sports betting analytics and trading. We're hiring Machine Learning Engineers across our core ML engineering and horse racing teams. You'd be designing, building and productionising ML pipelines, tooling, visualisation, frameworks and data engineering workflows to support strategy research, analysis and development, working closely with our quantitative research teams to turn prototype trading models into production-ready systems. You'd also help shape the high-level architecture of our strategy software so it scales effectively and keeps trading latency low.
We operate a hybrid Python/C++ engineering stack. A large portion of our stack is Python-based (utilising libraries like NumPy, SciPy, PyTorch, Polars, Ray, Plotly, and Dash), but an increasing amount of our most performance-critical systems are written in modern C++ (C++23). We are actively looking to expand our team's C++ expertise to drive these low-latency components forward.
The ideal candidate will have a strong software engineering background with a track record of building and maintaining production-grade ML pipelines. We are looking for engineers who are comfortable designing robust data engineering workflows, building reliable tooling, and writing clean, maintainable Python code alongside high-performance C++ components. You should be proficient in modern Python ML libraries while bringing solid C++ expertise to optimize our performance-critical architecture. Knowledge of common ML algorithms is a plus, but your primary strength should be in software design, performance optimization, and productionisation.
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) - learn more about your background + discuss the role
- Technical interview - Python & C++ software engineering assessment
- Full assessment day (10:00–5pm) - 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, Computer Science etc) from a top university
- Strong software engineering background in Python alongside solid expertise in modern C++ (C++23)
- Experience building, optimizing, and integrating low-latency performance-critical components in a hybrid Python/C++ environment
- Strong experience designing and maintaining ML pipelines and data engineering workflows
- Familiarity with modern engineering practices such as CI/CD, containerisation (e.g. Docker, Kubernetes) and automated testing
- Experience with cloud platforms (e.g. AWS, GCP or Azure)
- Comfortable working in a Linux environment
Nice to have:
- Advanced 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 deploying and serving ML models in production, including model monitoring and real-time inference
- Experience in scientific computing with other languages & frameworks
- Strong general high performance computing (multi-threading, networking, profiling and optimisation)
- Familiarity with Python data science tools and frameworks (e.g. NumPy, PyTorch, Polars)
Benefits:
- Participation in the company bonus scheme.
- 10% matched pension contributions
- Private healthcare insurance
- Long term illness insurance
- Gym membership
Senior Machine Learning Engineer (Python / C++) in London employer: Longshot Systems
Longshot Systems is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those passionate about technology and sports betting analytics. With a strong emphasis on employee growth, you will have the opportunity to develop your skills in a collaborative environment while enjoying the flexibility of a hybrid work model, including engaging in-person collaboration in our vibrant London office. Join us to be part of a forward-thinking team that values performance, creativity, and professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer (Python / C++) in London
✨Join Local Tech Meetups
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✨Contribute to Open Source Projects
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We think you need these skills to ace Senior Machine Learning Engineer (Python / C++) in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Longshot Systems.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Longshot Systems and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Longshot Systems
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Longshot Systems uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.