causaLens - Machine Learning Engineer
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Machine Learning Engineer

Hybrid
  • London, England, United Kingdom
  • London, England, United Kingdom
+1 more
Engineering

Job description

causaLens is the pioneer of Causal AI — a giant leap in machine intelligence.

We are on a mission to build truly intelligent machines, machines that truly understand cause and effect— it’s hard but super fun! If you want to build the future and are looking for a place that values your curiosity and ambition, then causaLens is the right place for you. Everything we do is at the forefront of technological advancements, and we are always on the lookout for people to join us whose skills and passion tower above the rest.

Since the company was established in 2017, causaLens has:
🥳Launched decisionOS, the first and only enterprise decision making platform powered by Causal AI - here

🚀Open sourced two of our internal tools and packages to support the open-source community, see Dara and Causal Graphs.

🦄Raised $45 million in Series A funding
🏆Been named a leading provider of Causal AI solutions by Gartner - here
🚀Included in Otta’s 2022 Rocket List as one of the fastest-growing companies to launch your career


At causaLens we are building the world's most advanced Causal AI powered decision intelligence platform for Data Scientists. The platform leverages state of the art Causal AI algorithms and models to empower data scientists and decision-makers to go beyond correlation-based predictions and have a real impact on the most important decisions for the business. Our platform is trusted and used by data science teams in leading organizations and provides real value across a wide variety of industries, and it's only the beginning.


Our Mission

To radically advance human decision-making.

A world in which humans leverage trustworthy AI to solve the greatest challenges in the economy, society and healthcare.
Head to our website homepage and watch the ‘Why Causal AI’ video to learn more.


The Role

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.


What you will do

We are looking for exceptional and ambitious individuals to develop our Causal AI platform. 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 and tabular data using Python, Cython, Numpy, Torch, etc.


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

Job requirements

  • This role is open for candidates with preferably 2+ years of experience

  • Strong academic record (Msc, Meng, Ph.D. 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, otherwise a good familiarity with Python is required

  • Ability to translate advanced machine learning algorithms into code - Python

  • An 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.

About causaLens
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 may be biased, but we believe you’ll be in good company. We offer a hybrid working setup and are dedicated to building an inclusive culture where diverse people and perspectives are welcomed. Aside from joining a smart and inspiring team, you’ll be amongst people who are always there to support your ideas and encourage you to grow. We celebrate our differences and come together to share our triumphs!

What we offer
We care about our people’s lives, both inside and outside of causaLens. Beyond the core benefits like competitive remuneration, pension scheme, paid holiday, and a good work-life balance, we offer the following:

  • Access to mental health support through Spill

  • Competitive salary

  • 25 days of paid holiday, plus bank holidays

  • Share options

  • Pension scheme

  • Happy hours and team outings

  • Referral bonus program

  • Cycle to work scheme

  • Friendly tech purchases

  • Office snacks and drinks


Logistics

Our interview process consists of a few screening interviews and a "Day 0" which is spent with the team (in-office). We will always be as transparent as possible so please don’t hesitate to reach out if you have any questions.

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