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Lead Machine Learning Engineer – SaaS – NLP – Remote – up to £110,000

Job description

Lead Machine Learning Engineer – SaaS – NLP – Remote – up to £110,000

The company

This business is creating the next generation of their SaaS invoice intelligence platform, which uses AI to uncover payment risks and deliver meaningful insights to some of the biggest companies across the world. They now have an exciting product roadmap ahead, expanding their product offering across fraud prevention and overpayments – driven by their strong Machine Learning department.
The Role

The product team of 25 is already well established, but as Machine learning lead, your role will be varied in managing 3 devs, while still being around 70% - 80 hands on. You’ll be mentoring, training, recruiting, and organising tasks as well as actually developing new ML models for a state of the art NLP project. You will be an individual with significant experience in Machine learning and demonstrated a track record of building NLP models previously. This platform will be used by clients such as Tesco, The hut group and other prestigious clients. This is a new greenfield project that will help finance teams in blue chip companies become more efficient with the way they deal with customers!

You’ll be responsible for assessing and introducing new technology, so there is ample opportunity for you to have a large impact on the business moving forward.

As the team grows, there will be several opportunities to progress your career as they have a big focus on nurturing learning and development.

Skills

  • At least 5 years of experience building ML models
  • At least one major project wjere you have built NLP models
  • Strong experience with Python, SQL & Git.
  • Experience leading and mentoring teams is desirable
  • A degree in a STEM subject – Masters or PHD would be preferred

Package
A salary of up to £110,000 + stock options!

Some of the team go in the office regularly, but as Team Lead you should be willing to visit the Central London office at least once a month.