Senior ML Engineer: Production ML Pipelines & Systems in London

Senior ML Engineer: Production ML Pipelines & Systems in London

London Full-Time 80000 - 100000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Design and build ML pipelines for sports betting analytics and trading.
  • Company: Longshot Systems, a leader in innovative sports tech.
  • Benefits: Competitive salary, flexible hours, and opportunities for growth.
  • Other info: Collaborative environment with a focus on innovation and impact.
  • Why this job: Join a cutting-edge team and shape the future of sports analytics.
  • Qualifications: Experience with Python, ML, and data engineering workflows.

The predicted salary is between 80000 - 100000 Β£ per year.

Longshot Systems is hiring a Machine Learning Engineer to design, build and productionise ML pipelines for sports betting analytics and trading.

The role involves working with Python ML stack, data engineering workflows, and productionising prototypes for scalable, low-latency strategy software.

You will collaborate with quantitative research teams, leverage Docker/Kubernetes, CI/CD, and cloud platforms, and contribute to robust data tooling and framework developments.

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Senior ML Engineer: Production ML Pipelines & Systems in London employer: Longshot Systems

Longshot Systems is an exceptional employer for those passionate about machine learning and sports analytics, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from opportunities for professional growth through hands-on experience with cutting-edge technologies like Docker, Kubernetes, and cloud platforms, all while contributing to impactful projects in the fast-paced world of sports betting. Located in a vibrant tech hub, the company provides a stimulating environment where creativity and technical expertise thrive.

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Contact Details:

Longshot Systems Recruitment Team

We think you need these skills to ace Senior ML Engineer: Production ML Pipelines & Systems in London

Machine Learning
Python
Data Engineering
Productionising Prototypes
Scalable Software Development
Low-Latency Systems
Docker