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. We have open sourced two of our internal tools and packages to support the open-source community. We raised $45 million in Series A funding and have been named a leading provider of Causal AI solutions by Gartner. We were also 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.
The Role
We are looking for exceptional and ambitious individuals to develop our Causal AI platform. We are looking for motivated and high-achieving Senior Backend Software Engineers, based in London, to join our Engineering team. This is a full-time placement with significant opportunities for non-linear growth.
Your focus will be on designing, implementing and maintaining our multi-tenanted, multi-cloud data science platform. You’ll be responsible for service and API design, backend python implementation, CI/CD rollout and meeting quality standards. Your remit will include multiple aspects of our multi-service platform, from AuthN to Data Integration and flow orchestration.
The broader application stack includes Python, FastAPI, Postgres, Github, Kubernetes, Helm, Terraform, AWS, GCP, Azure and other technologies.
A day in the life of the role:
- Collaborate closely with product managers, team leads and other senior engineers to understand the needs and requirements of services.
- Design and implement APIs, services and packages to help meet user’s needs.
- Develop and enhance CI/CD flows, improving quality, accountability and standards across the product stack.
- Work directly on integrating key elements of MLOps workflow with causal AI capabilities, ensuring robustness, scalability, and efficiency.
- Collaborate with cross-functional teams including data science, software engineering, and product to align technical solutions with business objectives and user needs.
This role offers a unique opportunity to leverage expertise in both Cloud Native Infrastructure and Python engineering to ensure the users spend their time building value and not setting up systems. If you are passionate about building smooth running systems that break down and simplify complex flows, we encourage you to apply and contribute to our team.
You have:
- Bachelor's or Master's degree in Computer Science, Physics, Maths, or a related field or equivalent industry experience.
- 3-5 years of professional experience in a production python cloud application, machine learning engineering, or a related role, with exposure to deploying machine learning models into production.
- Demonstrably strong Python skills with experience in distributed systems.
- Strong knowledge and experience with Cloud Native Infrastructure (GCP, Azure, AWS) with demonstrable skills in using and managing Kubernetes clusters.
- Good knowledge of DevOps tools and technologies, such as Helm, Docker, Terraform and CI/CD pipelines (GitHub Actions).
- Knowledge of MLOps especially on cloud environments: Vertex, Sagemaker, Synapse, is a huge plus.
- Strong Knowledge of the software development lifecycle (code review, version control, tooling, testing, etc.).
- Understanding of the full stack would be ideal (REST backends and SPA frontends).
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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