Senior Software Engineer - MLE

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 MissionTo 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 seeking a talented individual with a unique blend of Machine Learning Engineering and Data Science experience to join our team in a role focused on optimizing the path to production for Data Scientists. This role will primarily involve empowering Data Scientists to independently deploy their work into production.

A day in life:

• Collaborate closely with data scientists to understand their workflow challenges and requirements for deploying their work into production.

• Develop and enhance mechanisms and processes to streamline the integration of causal AI models into the MLOps workflow, customizing it to suit causality.

• Design and implement tools, visualizations, and mechanisms that empower data scientists to deploy their work into production autonomously, reducing dependencies on additional teams or assistance.

• Work directly on integrating key elements of MLOps workflow with causal AI capabilities, ensuring robustness, scalability, and efficiency.

• Act as a subject matter expert on processes and best practices, providing guidance and support to data scientists on deployment and monitoring.

• Collaborate with cross-functional teams including data science, software engineering, and product to align technical solutions with business objectives and user needs.