Forter is looking for a Senior Engineer with broad experience of the full machine learning life cycle to join our growing ML Platform team. 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. 

Forter is the world’s leading and most accurate provider of fully automated, real-time e-commerce fraud prevention. We protect many of the world’s largest merchants and marketplaces, providing them with approve/decline decisions backed by our chargeback guarantee. 

ML is central to Forter’s work. In 2020 alone, it enabled us to process e-commerce transactions worth over $200B, making decisions in real time, identifying fraud rings and quickly detecting new attack methods. Precision is crucial - bad decisions by our models cost us directly, and put money into the pockets of fraudsters.

Our adoption by merchants around the world provides us with billions of fresh data points each day. Our team of data scientists, analysts and cyber intelligence specialists continually identify new signals, engineer new features and research new models. But as the volume of data and  the number and complexity of models grows, so do the engineering challenges. 

If this kind of working environment sounds exciting to you, if you understand that Engineering is about building the most effective and elegant solution within a given set of constraints  - consider applying for this position. But hold on, you’d best check the position requirements first :) 

 

Stuff you’ll be doing:

  • Designing, building and maintaining the ML infrastructure that allows Forter’s models to make billions of real-time decisions every year. 
  • 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.
  • Handling distributed data proLessing pipelines to support model development.
  • Expanding the pool of internal customers able to use ML at Forter. Working 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.

Stuff we need you to have:

  • 2+ years experience bringing ML projects to production in a robust and reliable way. 
  • Familiarity with machine learning concepts and frameworks. 
  • Experience with large scale data processing, ideally with Apache Spark.
  • 3+ years developing complex software projects (Python / Ruby / Go / etc.)
  • 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

 

Projects you’ll work on:

We have a ton of important work to do, which is why we’re hiring! Our projects are of course changing all the time, but here are a few that we’ve either done in the past or are planning for the near future, so you can get an idea of the types of work we do. 

 

  • Develop reusable infrastructure and methodology that lets us bring new models to Production faster, without reinventing the wheel for each new business use case. 
  • Designing and delivering our Data Scientists’ research environment, for instance by providing experiment tracking, distributed hyperparameter search and great EDA tooling.  
  • Improve our ability to detect fraud by supporting ambitious ML projects with complex data requirements. 
  • Find solutions for effectively monitoring our models’ performance and context drift. Fraud prevention presents unique challenges here; most ‘ground truth’ labels arrive months after the prediction, and for transactions we decline they never arrive at all. 
  • Provide tools to quickly assess the impact of new features, prior to bringing them to production.
  • Make it trivial for our analysts to retrain models and get the newly trained models into production. 

It’d be really cool if you also:

  1. Have worked with MLops platforms such as MLflow, Metaflow or Kubeflow
  2. Are familiar with Databricks, Azure ML or Sagemaker.
  3. Have used a feature store. 
  4. Are comfortable in a containerized environment. 

 

 

At Forter, we believe unique people create unique ideas, and valuable experience comes in many forms. So, even if your background doesn't match everything we have listed in the job description, we still encourage you to apply and tell us why your skills and values could be an asset to us. By welcoming different perspectives, we grow together as humans and as a company.




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