Research Engineer - Causal AI
Sep 14, 2023
London - Hybrid, England, United Kingdom
causaLens is the pioneer of Causal AI — a giant leap in machine intelligence.
We are on a mission to build truly intelligent machines — 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
🦄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
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.
We are looking for a motivated and high-achieving Research Engineer based in London to join our Causal AI team in building the world's most sophisticated platform for Causal AI. This is a full-time placement with significant opportunities for personal development
Role and Responsibilities
This is a terrific opportunity to join a team composed of 6 PhD Research Scientists in Causal AI as the team's first Research Engineer.
Your job will be to develop packages for Causal Discovery, Causal Treatment Estimation, Structural Causal Models, Decision Engines, etc. You will be using Python, Cython, Numpy, Scikit-Learn, Torch, etc. You will work closely with the Research Scientists but your focus will be on implementing, refactoring, maintaining and testing the packages as opposed to conducting the research.
Proven track record of delivering machine learning research or projects
Ability to translate advanced machine learning algorithms into code - and high degree of productivity in Python
Familiarity with the Python numerical computing and machine learning package ecosystem
In-depth understanding of computer architecture is preferable, e.g. C, C++, Cython
Strong familiarity with the software development life cycle (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.
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
Annual Discretionary Bonus
25 days of paid holiday, plus bank holidays
Happy hours and team outings
Referral bonus program
Cycle to work scheme
Friendly tech purchases
Office snacks and drinks
Our interview process consists of a few screening interviews and a "Day 0" which is spent with the team (either in the office or virtually, whatever you feel comfortable with). We will always be as transparent as possible so please don’t hesitate to reach out if you have any questions