What you will be doing:
Designing, building, and maintaining the ML infrastructure that allows models to make billions of real-time decisions every year.
Building a platform that enables managing a full ML model lifecycle – from researching to training, deploying, and serving predictions in real-time.
Building distributed data processing pipelines to support model development.
Acting as a consultant to researchers, data scientists, and expert analysts and enabling them to research new models faster and with greater precision by providing cutting-edge tooling.
Expanding our ML infrastructure to make it scalable, quick, and efficient to bring diverse models to production and to monitor their performance and drift over time.
Expanding the pool of internal customers able to use ML . Work with them to understand their needs and help them make the most of the infrastructure that well provide.
Acting as an advocate for MLOps, continually improving our processes, and raising our standards.
4+ years experience with large-scale data processing, ideally with Apache Spark.
5+ years developing complex software projects with at least one of general-purpose languages (preferably Python, but not a must)
Backend and server-side development experience of complex, highly scalable systems
Experienced with machine learning concepts and frameworks.
Motivation to understand the needs of internal users, provide them with great tooling, and teach them how to use it.
Experience working with public clouds (AWS / GCP / Azure)
Fluent in written and spoken English
