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Machine Learning Engineer

causaLens
London
7 months ago
Applications closed

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Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

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

Do you have the right skills and experience for this role Read on to find out, and make your application.

We are on a mission to build truly intelligent machines that 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. We have open-sourced two of our internal tools and packages to support the open-source community. We have raised $45 million in Series A funding and have been named a leading provider of Causal AI solutions by Gartner. Included in Otta’s 2022 Rocket List as one of the fastest-growing companies to launch your career.Our MissionTo radically advance human decision-making through 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 RoleWe are looking for a motivated and high-achieving Machine Learning Engineer based in London to join our Product team in building a platform to optimize 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-caliber, mission-driven team building technology that improves our world.

What you will doAs a machine learning engineer in the Product team, you will work alongside software engineers and scientists to develop our Causal AI platform. A successful candidate will 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.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 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 causaLensCurrent 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 various industries.We offer a hybrid working setup and are dedicated to building an inclusive culture where diverse people and perspectives are welcomed. We celebrate our differences and come together to share our triumphs!

What we offerAccess 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.LogisticsOur 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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