Head of Machine Learning Engineering Lab - EdTech Unicorn

City of London Permanent
  • Opportunity for ML Expert to influence digital learning and social good
  • Tech Lead for ML & NLP Innovation Lab to develop this digital learning product

About Our Client

Michael Page is delighted to be working exclusively with the world's most valuable multi-national EdTech Unicorn business, BYJU'S.

Within a decade of its launch, BYJU'S have rapidly expanded to now cater to a large student community globally where it has a presence in over 120 countries, impacting millions of learners worldwide. The mission is to ultimately create better learning outcomes, for ALL students.

With a core set of digital products already creating a dent in the education arena the need and opportunity to further innovate and evolve those products to better support their user base is clear to see. BYJU'S are looking to revolutionise the digital learning pathways for children all over the world.

Job Description

Having created a unique market within the developing world, demand has significantly increased in the west and hence the client is now looking to create a world-class innovation hub in London.

As Tech lead, you will be spearheading the new leadership function focussed on innovation and 'best in class' service. The EdTech arena requires deep personalisation and constant evolvement, however, you will inherit a client who is already rich with data but it's now about developing this personalised journey across the spectrum.

With so many touch points available, you will literally be inundated with information where you will be working with terabytes of text, images, and other types of data to solve real-world problems. The magic is making this come alive and create unique experiences that will enhance the student on their journey and ultimately become a success in their chosen field.

As London's leader you will be building a team of world-class ML / NLP engineers around you, but ultimately bringing your deep ML knowledge where your role will include but not be limited to the following:

  • Provide end-to-end architecture/solution guidance to ML Engineering and Data Ontology teams.
  • Work with various Insight and other product teams to implement complex solutions.
  • Stay current on various ML, AI, NLP and ECM practices/technologies.
  • Collaborate with our data scientists to create scalable ML solutions for business problems
  • Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes
  • The challenge is building a world-class team from London.

The Successful Applicant

All industry backgrounds are encouraged to apply, the key desire is wanting to make a difference to our younger generation and presents an opportunity to give something back for social good. The ideal candidate will have:

  • Masters or PhD degree in computer science, or related technical, math, or scientific field
  • Strong working knowledge of deep learning, machine learning and statistics.
  • Hands-on experience building models with deep learning frameworks like MXNet, Tensorflow, Caffe, Torch, Theano or similar. Probabilistic modelling / Bayesian inference
  • Hands on experience with deep learning NLP (e.g., CNN, RNN, LSTM)
  • Seq2Seq (deep Sequence to Sequence)
  • Computer vision (generative models - text to video)
  • Experience in using Python, R or Matlab or other statistical/machine learning software
  • Strong communication and data presentation skills
  • The motivation to achieve results in a fast-paced environment.
  • Experience with statistical modelling / machine learning
  • Ability to think creatively and solve some of the most challenging problems



What's on Offer

In return, you will be offered a superb salary and compensation package with excellent benefits. The role will require regular meetings in London so commuting to Kings Cross and surrounding areas will be required.

Contact
Michael Warren
Quote job ref
JN-082021-2957854

Job summary

Location
Contract type
Consultant name
Michael Warren
Job reference
JN-082021-2957854