Senior Full Stack Engineer - MLOps

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causaLens are the pioneers of Causal AI — a giant leap in machine intelligence.

We build Causal AI-powered products that are trusted by leading organisations across a wide range of industries. Our Causal AI Platform empowers all types of users to make superior decisions through intuitive user interfaces and APIs that adapt to their level of technical expertise. We are creating a world in which humans can trust machines with the greatest challenges in the economy, society, and healthcare.

We are looking for motivated and high-achieving Senior Fullstack Software Engineers focusing on bringing causality, explainability and accountability to MLOps as a first on-the-ground engineering member of our CausalOps team, joining product and data scientists.

We are a mission-driven, interdisciplinary team with an inclusive culture building technology that improves our world. This is a full-time placement with significant opportunities for growth in a rapidly expanding team.

Roles and Responsibilities

As a Senior Full Stack Engineer, you will be involved with the product at all stages of development, from initial conception of a feature all the way to being deployed to our customers. You should have strong technical and communication skills and should want to take ownership of what you are building. You will be expected to push forwards your own ideas as well as be comfortable mentoring and coaching junior members of the team.

What You’ll Be Working On

You will be expected to work across our application stack and be willing to learn any areas which you do not already have experience with. Our primary languages are Python for backend and machine learning code on FastAPI based apps, with Typescript + React for our frontends.

Your primary focus will be streamlining the operationalisation of causal machine learning models, the workflows for delivering models, as well as the dashboards and system processes to view and understand how models are performing. Accelerating the workflow of data scientists and ML Engineers. Removing obstacles in their way to delivering real value to their customers.

You will be helping us advance the state of the art of MLOps by bringing the strengths of causal AI to bear to build leading indicators of model sensitivity, visibility on model recourse and A/B testing.

Our infrastructure runs on Kubernetes, familiarity with cloud services, docker and modern CNCF stacks is desirable.