MLOps Engineer: Deploy & Scale ML in Production (Remote) in Edinburgh

MLOps Engineer: Deploy & Scale ML in Production (Remote) in Edinburgh

Edinburgh Full-Time 63000 - 77000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Deploy and maintain ML models, optimise pipelines, and ensure AI solutions' reliability.
  • Company: Techwaka, a forward-thinking tech company based in Edinburgh.
  • Benefits: Remote work, competitive salary, and opportunities for professional growth.
  • Other info: Collaborate with data scientists and software engineers in a supportive environment.
  • Why this job: Join a dynamic team and shape the future of AI technology.
  • Qualifications: Strong Python skills and 3+ years of relevant experience required.

The predicted salary is between 63000 - 77000 Β£ per year.

Techwaka in Edinburgh, United Kingdom, is seeking a Machine Learning Engineer to join our MLOps team.

You will deploy, monitor, and maintain ML models in production, optimize pipelines, and contribute to scalable AI infrastructure.

You will collaborate with data scientists and software engineers, implement CI/CD for ML, and ensure reliability of AI solutions across cloud platforms such as AWS, GCP, and Azure.

A strong Python background and 3+ years of relevant experience are required. #J-18808-Ljbffr

MLOps Engineer: Deploy & Scale ML in Production (Remote) in Edinburgh employer: Techwaka

Techwaka is an exceptional employer that prioritises employee growth and development, offering a supportive work culture where leadership and coaching are at the forefront. Located in Slough, UK, we provide competitive benefits including UK visa sponsorship and a pension, making it an ideal place for those seeking meaningful and rewarding employment in customer service.

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Contact Details:

Techwaka Recruitment Team

We think you need these skills to ace MLOps Engineer: Deploy & Scale ML in Production (Remote) in Edinburgh

Machine Learning
MLOps
Python
CI/CD
Cloud Platforms (AWS, GCP, Azure)
Pipeline Optimization
AI Infrastructure