Adeel Nadeem

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Machine Learning Engineer - MLOps

Ref #: CW CAM ML
Adeel Nadeem 15/02/2022
Location: Cambridge, Cambridgeshire Not Disclosed Cambridge, Cambridgeshire
Salary: £45,000 - £80,000 + Benefits £
Type: Permanent
Seniority: Associate
Date: 15/02/2022
Machine Learning Engineer - MLOps

Do you want to join an undisputed market leader within AI where the market size is set to explode from £150 million to £8 billion in the next 7 years?

Our modern world is brimming with devices that are more intelligent and tailored to our human needs, and this technology is taking these products to the next level – from health and wellbeing to safety and security. The Machine Learning Engineer will have the opportunity to join at an exciting stage of growth, being named as one of the most innovative AI companies.

As a Machine Learning Engineer, your work will revolve around producing the machine learning models, which are fundamental to the product having an impact across millions of consumers. You will use the latest machine learning techniques to train, improve and evaluate models, as well as working with huge datasets. The Machine Learning Engineer will be working collaboratively with multiple touch points across the business including - product, QA, research, software and data teams.

Machine Learning Engineer Requirements:

  • A STEM degree with a final grade of at least 2:1 + at least one year of relevant work experience in industry.

  • Knowledge of Python / Numpy / Pandas.

  • Knowledge of applying machine learning or statistical techniques to real-world problems.

  • Exemplary written and verbal communication skills.

  • Experience with Keras /TensorFlow or Pytorch, MLOps, embedded computing, using AWS, data visualisation tools nice to have.

This market for intelligent AI may be new, but this innovation has attracted great interest and excitement for its possible benefits in many areas of daily life. As a Machine Learning Engineer, your skills and experience will progress the technology even further and positively impact millions, whilst offering extensive career progression opportunities. Apply now for immediate consideration. This role could be hybrid or fully remote.

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