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VP of Engineering at causaLens

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  • London
  • fulltime
  • -
  • Summary

    causaLens are the pioneers of Causal AI — a giant leap in machine intelligence.

    We build Causal AI-powered products that are trusted by leading organizations across a wide range of industries. Our No-Code Causal AI Platform empowers all types of users to make superior decisions through an intuitive user interface. We are creating a world in which humans can trust machines with the greatest challenges in the economy, society, and healthcare.

    We are looking for a motivated and high-achieving VP of Engineering based in London to join the team on our vision 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

    The VP of Engineering will lead the Engineering Group in causaLens. This is a high responsibility role in our company and has potential for a large impact. The product that you would be heading is important and market-changing. This position is suitable for an experienced engineering manager or an extremely talented and experienced team lead who wants to grow into an engineering management role.

    The application stack is composed of Python, Numpy, Scipy, Sklearn, XGBoost, Keras, Django, Celery, Postgres, Redis, Ansible, AWS, GCP, and other technologies.

    Day-to-day responsibilities
    Broadly, you will be a combination of the following parts:
    Engineer
    :

    • You will be responsible for architectural and structural decisions, writing of specifications, design of APIs, etc.
    • You will have to review important, high-impact PRs, especially ones that have to do with data flow
    • You will occasionally write code for important, high-impact components

    Scientist:

    • You will keep the big picture view of the entire machine learning framework that combines a big variety of subsystems, techniques and technologies
    • You will design novel machine learning architectures and algorithms, and occasionally develop them
    • You will have to review important, high-impact PRs that have to do with AutoML, causal discovery, machine learning pipelines, metrics, etc.

    Product manager:

    • Run daily standup meetings with the team, assign tasks and manage deliverables
    • Interact with other parts of the business and our CEO and CTO in order to:
    • Discover new product opportunities
    • Target the roadmap
    • Build long term roadmap for the product(s)

    People manager:

    • Have regular 1-1 check-ins with the team
    • You will ensure that the team is sufficiently trained
    • You will hire new members of the team

    What would my first 3 months look like?

    During the first 3 months, you would work very closely with Max (our CTO) to train for this role, establish processes and ensure a smooth transition to leading the team entirely by yourself.

    The Company

    Current machine learning approaches have severe limitations when applied to real-world business problems and fail to unlock the true potential of AI for the enterprise. causaLens is pioneering Causal AI, a new category of intelligent machines that understand cause and effect - a major step towards true artificial intelligence. Our enterprise platform goes beyond predictions and provides causal insights and suggested actions that directly improve business outcomes for leading businesses in asset management, banking, insurance, logistics, retail, utilities, energy, telecommunications and many others.

     

    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

    • Best Deeptech Company 2019 - Artificial Intelligence Awards
    • ‘Meet causaLens, a Predictive AI For Hedge Funds, Banks, Tech Companies’ – Yahoo Finance
    • ‘The U.K.’s Most Exciting AI Startups Race To Scale’ - Forbes
    • AllianzGI Taps Virtual Data Scientists amid War for Talent’ - Financial Times
    • ‘Machine Learning Companies to watch in Europe’ - Forbes
    • Best Investment in Deeptech’ award - UK Business Angels Association awards
    • ‘100 Most Disruptive UK Companies’ - Hotwire
    • ‘causaLens Appoints Hedge Fund Veteran and Data Leaders to Advisory Board’ - Newswire

    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 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 successful candidates.

    Job requirements

    • Academic background in Computer Science or a related quantitative field
    • Engineer:
      • Thorough understanding of computer systems at a broad level: data flow, distributed systems, numerical computing, frontend, web applications
    • Scientist:
      • Deep understanding of the broad fields of machine learning, statistics and mathematics. Attention to detail.
    • Product manager:
      • Capability to plan and execute complex and sizable projects
      • Prior experience building products is a plus
    • People manager:
      • Empathy and people skills
      • Experience in leading engineering teams is a plus
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