Senior Machine Learning Engineer (Python / C++)

Longshot Systems; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Participation in company bonus scheme

10% matched pension contributions

Private healthcare insurance

Long term illness insurance

Gym membership

Job summary

Longshot Systems in London is seeking Machine Learning Engineers to design, build and productionise ML pipelines and data workflows to support strategy research and development. You will work on a hybrid Python/C++ stack, optimize low-latency components, and shape the architecture of trading analytics software, collaborating with quantitative research teams.

The role offers a hybrid work model with a London office and flexible hours, and opportunities to work across core ML engineering and horse

Qualifications

• A degree in a quantitative, technical subject 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 CI/CD, containerisation (Docker, Kubernetes) and automated testing.
• Experience with cloud platforms (AWS, GCP or Azure).
• Comfortable working in a Linux environment.

Responsibilities

• Design, build and productionise ML pipelines, tooling, visualisation, frameworks and data engineering workflows to support strategy research, analysis and development.
• Collaborate with quantitative research teams to turn prototype trading models into production-ready systems.
• Shape the high-level architecture of our strategy software to scale and reduce trading latency.
• Work with a hybrid Python/C++ engineering stack, writing clean Python and high-performance C++ code.

Skills

Python

C++23

ML pipelines

Data engineering

CI/CD

Docker

Kubernetes

Cloud platforms

Linux

Education

Bachelor's degree in a quantitative field

Job description

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 optimise our performance-critical architecture. Knowledge of common ML algorithms is a plus, but your primary strength should be in software design, performance optimisation, 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