Want to create positive impact through design?

You’ve operationalized machine learning while building scalable, robust, and secure products. A keen problem solver, use technology to work out complex analytical problems, and have:

• been exposed to different stages of machine learning system design and development
• utilized tools for machine learning pipeline management and monitoring (for example, MLflow, Pachyderm, Kubeflow, Seldon, Grafana)
• gained familiarity with automation and deployment (CircleCI/Jenkins/github actions, etc) and infrastructure as code (Terraform, CloudFormation, etc) technologies
• employed distributed processing frameworks such as Spark and Dask, and interacted with cloud platforms and container technologies
• gained practical knowledge of software engineering concepts and best practices, like testing frameworks, packaging, API design, DevOps, DataOps and MLOps
• developed excellent problem-solving skills and easily adapt to new technologies, trends, and frameworks
• gained an advanced degree in computer science, engineering, or mathematics, or have equivalent experience

You have a degree in computer science, mathematics, physics, engineering and a passion for producing high-quality code. You’ll also:

• have experience using tools like Python, Kedro, AWS, Azure, Databricks, Docker, Kubernetes, Django, Flask, and MySQL / Postgres
• advocate using the right tech for the right task—you’ll be up to date with the latest technologies and ensure we make the relevant changes when needed
• believe in iterative change, enjoy experimenting with new approaches, as well as learning and improving to move forward faster
• be highly collaborative, capable of putting aside your own agenda and listening and learning from colleagues
• have natural enthusiasm and enjoy sharing your passion with others