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Head of Machine Learning and Data engineering at Algomo at Algomo

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  • London
  • fulltime
  • ₤50000 - ₤75000 per year
  • -
  • Role: Head of Machine Learning / Data engineering

    Location: Remote or London (preferred). Must be UK tax-registered

    Schedule: Full-time, permanent, flex-working ⏰


    The company

    Algomo is a multilingual chatbot engine that provides instant resolutions to customer and employee queries in any language.

    We have developed a unique technology that is fluent in 109 languages. All the other commercial players (including Google, Microsoft, Amazon, IBM etc) combined support just 33. With the additional 76 languages, we are practically a monopoly for 1.3 Billion people, mainly living in emerging economies.

    Our mission is to facilitate access to digital goods to anyone in the world, no matter what language they speak.

    Algomo was founded in February 2020, by a technical CEO (ex VP of Data Science at Barclays), has a working MVP, and has received $600.000 in grant funding so far - all the equity still belongs to the founders - so there's a really high upside for you to join at this time.

    Here is a 2-minute video demonstrating how the technology works.

    The role

    We are looking for a Senior Natural Language Processing Engineer to lead our Machine Learning team in the development of new features. This senior role will work closely with the CEO, Tech lead and other team members in the development of great features for our customers

    You'll need to be someone who is willing to be completely hands-on but should also lead our Junior Data Scientist.

    For the first few months, you will be working on a government-backed project that uses human in the loop pipelines to distil human knowledge into a topic modelling algorithm. The results of that work will be published in academic journals, alongside our academic partner from Brunel University.



    • Research academic literature and ensure that our algorithms and approach are in line with current trends.
    • Build and expand on the existing NLP algorithms
    • Develop robust ETL pipelines and automated processes for ingesting and processing data.
    • Leading the research roadmap and Data Science team. Scoping, prioritising and managing multiple data science projects in parallel with the capacity for getting things done, be it either hands-on or by leading others

    Qualifications / Skills

    • Master’s/PhD in CS, Engineering, Physics, Mathematics, or similar fields
    • 3-4 years of experience in Natural Language Processing.
    • Expert in Python, 
    • Skilful in TensorFlow and Keras
    • Ability to write production-ready code
    • Experience in AWS 
    • Working experience in MLOps, developing production data pipelines and productionising data-science models
    • Excellent communication skills with a variety of technical and non-technical audiences
    • Excellent knowledge of machine learning methods, as well as deep understanding of probability and statistics
    • Familiarity with tools like Airflow, MLFlow, Docker, and distributed computing is a plus
    • Ideally some previous startup experience, and/or a range of experiences within larger companies


      • Competitive Salary 
      • Flexible working hours - as long as the work gets done, we're happy. ?
      • Remote first (we're a fully distributed team, but you need to be a UK tax resident)
      • 25 days holiday per year, in addition to 8 bank holidays. You can also roll over up to 10 days of holiday per year
      • Meaningful Equity - everyone in the team owns part of the business 
      • RnD time: 10-20% of your time will be spent on keeping up to date with recent ML advancements. You will also have the chance to author ML papers.

    Our recruitment process

    We have a 3 stage interview process:

    1. CV screening where we will get in touch with you if we believe it's a good fit. 
    2. An informal 30 minute chat, to get to know each other (all pass here)
    3. A take-home test that should take around 10hrs max
    4. A follow-up interview to discuss the solution with the team and assess cultural fit
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