Senior ML Engineer: Production ML & MLOps Lead

Senior ML Engineer: Production ML & MLOps Lead

Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
Houseful Limited

At a Glance

  • Tasks: Transform POC model code into robust pipelines and live APIs for production.
  • Company: Houseful Limited, a forward-thinking tech company in Greater London.
  • Benefits: Flexible working, 25 days annual leave, and a discretionary bonus.
  • Other info: Join a dynamic team with opportunities for growth and innovation.
  • Why this job: Lead the deployment of ML models and create impactful solutions for customers.
  • Qualifications: Strong Python skills and experience in data engineering required.

The predicted salary is between 60000 - 80000 Β£ per year.

Houseful Limited in Greater London is seeking an experienced Senior Machine Learning Engineer to translate POC model code into robust pipelines and live APIs. You will oversee the deployment of ML models into production and work with cross-functional teams to integrate solutions.

The ideal candidate has strong Python experience, familiarity with data engineering, and is passionate about building products that meet customer needs.

Benefits include:

  • Flexible working
  • 25 days of annual leave
  • Discretionary annual bonus

Senior ML Engineer: Production ML & MLOps Lead employer: Houseful Limited

Houseful Limited is an excellent employer located in the vibrant Greater London area, offering a dynamic work culture that fosters innovation and collaboration. With a strong emphasis on employee growth, you will have access to flexible working arrangements, generous annual leave, and a discretionary bonus, making it an ideal place for those looking to make a meaningful impact in the field of machine learning.

Houseful Limited

Contact Details:

Houseful Limited Recruitment Team

We think you need these skills to ace Senior ML Engineer: Production ML & MLOps Lead

Machine Learning
Python
MLOps
Data Engineering
API Development
Pipeline Development
Cross-Functional Collaboration