• Forter is looking for a Senior Engineer with a data engineering background to join our growing ML Platform team
• This is a great opportunity, whether you have experience with ML and are looking for a ML focused product or are an experienced Data Engineer looking to enter the world of ML
• 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
• Are familiar with Databricks or Airflow

Desirable

• Together we’ll provide tools to develop more effective models, get them into production faster, and ensure that they continue to perform well over time
• You’ll be part of a highly proficient engineering team that is a focal point for all ML engineering activity, striving to constantly bring innovation and leverage ML capabilities across all company teams and products
• This role presents a unique opportunity to enter the ML domain. For those already experienced in ML infrastructure, it offers the chance to grow within a team that specializes in high-scale, Big Data and ML systems
• Designing, building, and maintaining the ML infrastructure that allows Forter’s 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 at Forter. Work with them to understand their needs and help them make the most of the infrastructure that we’ll provide
• Acting as an advocate for MLOps, continually improving our processes, and raising our standards