Connecting linkedin

W1siziisimnvbxbpbgvkx3rozw1lx2fzc2v0cy9oyw1sew4td2lsbglhbxmvanbnl2jhbm5lci1kzwzhdwx0lwpvyi5qcgcixv0

Job

Machine Learning Engineer

  • Location

    London

  • Sector:

    Technology

  • Job type:

    Permanent

  • Contact:

    Deian Rees

  • Contact email:

    d.rees@hamlynwilliams.com

  • Salary high:

    0

  • Salary low:

    0

  • Published:

    about 1 month ago

  • Expiry date:

    2021-11-25

  • Startdate:

    ASAP

We’ve partnered with a global, market leading InfoTech organisation whose platform is used by almost 70% of the population. They seek to create life-changing interactions between humans and online services with new and unseen solutions.

 

As their newest Data Scientist, you will have a hands-on impact on the software they produce, dealing with challenges of deploying machine learning models at large scale. You will help teams orchestrate their machine learning pipelines, making sure the end customer benefits are tangible and impactful, predicting and detecting fraudulent messages, optimizing the best time to send messages, improve CX with recommendations for best product or service.

 

Responsibilities:

  • Deploy complex machine learning models to a variety of output environments in a B2B and B2C settings
  • Understand, explore and industrialize the entire A to Z data journey process to ensure data scientists get the data they need, when they need them, at the best possible quality
  • Write well designed, testable, and scalable code in accordance with Infobip engineering code principles
  • Have a general overview and understanding of the interactions and dependencies in the entire system
  • Regularly contribute to discussions and brainstorming with high quality ideas that result in adoption and improvements

 

Requirements:

  • Good knowledge and skills working with SQL, Linux, and Python
  • Expertise through exposure and use of popular machine learning operations (MLOps) toolkits and frameworks, including vendors’ offerings (AWS Sagemaker, MSFT Databricks, ML Studio) and open source solutions (e.g., MLflow.org, automl.org)
  • Knowledge and understanding of containerization technologies (e.g., Kubernetes, Docker)
  • Exposure to AWS and/or Azure machine learning services
  • Data Science Background

 

Role is completely remote.

 

If this is of interest please apply below, or contact Deian Rees at d.rees@hamlynwilliams.com

 

#LI-DR1