Director of ML Engineering

Job description

Summary

We are looking for a motivated and high-achieving Director of ML 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.


The Company

causaLens is pioneering a completely new approach to time-series prediction. Its Enterprise Platform is used to transform and optimise busineses that need accurate and robust predictions – including significant businesses in finance, IoT, energy and telecoms. Almost all current machine learning approaches, including AutoML solutions, severely overfit on time-series problems and therefore fail to unlock the true potential of AI for the enterprise. causaLens was founded with the mission to devise Causal AI, which does not overfit, and so provides far more reliable and accurate predictions. The platform also includes capabilities such as autonomous data cleaning and searching, autonomous model discovery and end-to-end streaming productisation.


causaLens is on a mission to build truly intelligent machines that go beyond current machine learning approaches - a curve-fitting exercise. Devising Causal AI has allowed us to teach machines cause and effect for the first time - a major step towards true AI.


causaLens is run by scientists and engineers, the majority holding a PhD in a quantitative field. For more information visit www.causaLens.com or contact us on info@causaLens.com. Follow us on LinkedIn and Twitter.


causaLens in the News


Roles and Responsibilities

The Director of Engineering will lead the Product 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.

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 couple of interviews and an on-site visit. We will do our best to transparently communicate the process with the 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