Hybrid ML Engineer — Sports Betting Analytics & Trading

Longshot Systems Ltd

Greater London

Hybrid

GBP 90,000 - 130,000

Full time

3 days ago
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Benefits offered by this job

Company bonus scheme
10% matched pension contributions
Private healthcare insurance
Long term illness insurance
Gym membership

Job summary

Longshot Systems Ltd is hiring Machine Learning Engineers to design, build and productionise ML pipelines, tooling, visualisation and data workflows to support strategy research and development. You will collaborate with quantitative researchers to convert prototype models into production-ready systems.

We operate a hybrid model with a London office, typically in Farringdon, and flexible remote days. Strong Python and modern C++ skills, plus experience with ML libraries, are essential for this

Qualifications

  • Degree in a quantitative or technical subject from a top university.
  • Strong Python and modern C++ (C++23) software engineering.
  • Experience building low-latency components in a hybrid Python/C++ environment.
  • Experience with ML pipelines and data engineering workflows.

Responsibilities

  • Design, build and productionise ML pipelines and data engineering workflows.
  • Help shape scalable high-performance architecture with low trading latency.

Skills

Python
C++ (modern)
Low-latency
ML pipelines
Data engineering
CI/CD
Docker
Kubernetes
AWS/GCP/Azure
Linux

Education

Bachelor's degree in a quantitative subject

Tools

Dagster
Prefect
Pandas
Polars
scikit-learn
PyTorch
TensorFlow

Job description

Longshot Systems Ltd is hiring Machine Learning Engineers to design, build and productionise ML pipelines, tooling, visualisation and data workflows to support strategy research and development. You will collaborate with quantitative researchers to convert prototype models into production-ready systems.

We operate a hybrid model with a London office, typically in Farringdon, and flexible remote days. Strong Python and modern C++ skills, plus experience with ML libraries, are essential for this

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