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Machine Learning Engineer
at causaLens

go back to Data and Product Jobs
  • London
  • fulltime
  • -
  • Summary

    We are looking for a motivated and high-achieving Machine Learning Engineer based in London to join our Product team in building a platform to optimise every business on the planet. This is a full-time placement with significant opportunities for personal development.

    We offer an intellectually stimulating environment, work within an interdisciplinary team and an inclusive culture. We are a high-calibre, mission-driven team building a technology that improves our world.

     

    Roles and Responsibilities

    We are looking for exceptional and ambitious individuals to develop our Causal AI platform for time series. You will work as a machine learning engineer in the Product team which is composed of software engineers and scientists. A successful candidate will also be able to showcase broader data science and software engineering skills.

    Your focus will be on feature engineering, machine learning, and building causal algorithms for time series using Python, Cython, Numpy, Torch, etc.

    The broader application stack includes Python, Cython, Numpy, Torch, Django, Celery, Postgres, Redis, Ansible, AWS, GCP, React and other technologies.

    This role is open for candidates of all seniority levels, junior to senior.

     

    Job Requirements

    • Strong academic record (Msc, Meng, PhD or PostDoc preferred)
    • Very advanced quantitative skills in machine learning/statistics/mathematics or similar fields
    • Development experience in at least one scripting language - preferably Python
    • Ability to translate advanced machine learning algorithms into code - preferably Python
    • In-depth understanding of computer architecture is preferable, e.g. C, C++, Cython
    • Knowledge of the software development life cycle is a plus (version control, tooling, testing, etc.)
    • Highly capable, self-motivated, collaborative and personable
    • Ability to demonstrate integrity and drive
    • Naturally curious, creative and effective problem solver with the ability to come up with ideas to tackle problems on the cutting edge
    • An excellent written and verbal communicator with a high level of business acumen
    • Ability to effectively work independently in a fast-moving environment
    • Ideally you should be able to work in London or be able to commute. Candidates outside of London who are interested in relocating will be considered.

     

    The Company

    causaLens is pioneering Causal AI, a new category of intelligent machines that understand cause and effect - a major step towards true AI. Its enterprise platform is used to transform leading businesses in Finance, IoT, Energy, Telecommunications and others.

    Current machine learning approaches, including AutoML solutions, have severe limitations when applied to real world business problems and fail to unlock the true potential of AI for the enterprise. For instance, in the case of predictions, they severely overfit and do not adapt when the environment changes. causaLens’ Causal AI Platform goes beyond predictions, providing transparent causal insights and suggesting actions that directly improve business KPIs.

    causaLens is run by scientists and engineers, the majority holding a PhD in a quantitative field. Contact us on info@causaLens.com or follow us on LinkedIn and Twitter.

    We are committed to addressing the diversity problem in the tech industry, and that starts with making sure we have a team where everyone feels at home and can contribute as a peer.

     

    causaLens in the News

     

    Benefits

    • The opportunity to join a fast-growing, agile, and international team passionate about innovation and making a difference
    • Competitive remuneration
    • Share option scheme
    • Pension scheme
    • 32 days paid holiday allowance (incl. bank holidays)
    • Equipment you need to get the job done (MacBook Pro etc.)
    • Good work-life balance
    • Opportunities for continued learning and self-development, including courses, conferences and book budget
    • Flexible work-from-home and remote days
    • Cycle to work scheme
    • Weekly journal club and knowledge sharing presentations
    • Regular team outings, pizza Thursdays and annual company retreats
    • Fruits, snacks and soft drinks in the office
    • Amazing, smart, fun and inspiring colleagues, always there to support your ideas, growth and enthusiasm

     

    Logistics

    Our interview process consists of a coding test, 2 screening interviews and a "Day 0" which is spent with the team. Normally the Day 0 takes place on-site but for the time being they will take place online.

    We will do our best to transparently communicate the process with the successful candidates.

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