Machine Learning Engineer (biometrics) - Remote

Simprints is a nonprofit tech company with a mission to radically increase transparency and effectiveness in global development. We build ethical, inclusive digital ID powered by biometrics to verify that health, aid, and services truly reach people. Simprints partners with organizations like Gavi to boost immunization rates in developing countries, Ministries of Health like Ghana on pandemic response, and NGOs like BRAC to deliver maternal healthcare. Studies have shown Simprints increases impact through real-time, precision data, for example increasing maternal health visits by 38% in Bangladesh or accurate HIV tracing by 62% in Malawi. Today we’ve worked in over 17 countries helping deliver health, aid, and finance to >2.5M people. Our goal is to transform the way the world fights poverty, ensuring that every vaccine, every dollar, and every public good reaches the people who need them most.

About the Role

As a Machine Learning engineer, you will be part of a remote-first agile team responsible for the end-to-end pipeline for our Machine Learning models in biometrics. This involves designing, developing, and deploying machine learning models. You will be a developing domain expert and expected to help influence the direction of Simprints development. You will partner with data scientists and engineers to develop and implement machine-learning solutions for real-world problems. Working with product managers, you will establish requirements and develop innovative solutions to the most complex challenges.

You will be working with a highly skilled set of engineers. As the business and team have grown rapidly, so has the emphasis on creating a team and structure that can enable us to continue to create innovative solutions and products.

It is absolutely imperative we find someone with Machine Learning skills who have worked on biometrics. If you have no experience working on biometrics, please do not apply for this role.

Location

This is a remote job; we are currently only able to take forward applicants based in the UK, Bulgaria, Romania, Hungary, Poland, Croatia, Ukraine, Latvia, Spain, Netherlands and Germany. The candidate must have the right to work in one of these countries.

We are unable to support relocation or visa sponsorship.

If you are not based in one of these countries, please do not apply for this role.

Salary

UK Grade 6: £55,000 - £75,000 with a cost-of-living adjustment for non-UK residents

Your Impact

At Simprints, we want everyone to feel ownership of the tasks they are working on, starting from your first day. As a Senior Machine Learning Engineer, you will be given a “north star” in the shape of a KPI (Key Performance Indicator) or goal, and you will be asked to devise a strategy to get there. In your first month, you will be given the resources you need to set up your environment and start learning about the Simprints biometrics platform. This will include access to our codebase, documentation, and data. You will have the opportunity to liaise with other Simployees to gain a good overview of the company and our goals. By your third month, you will be well on your way to defining requirements for creating machine-learning models for biometric data. This will involve understanding the current state of the solution, identifying areas for improvement, doing intensive research and gathering stakeholder feedback. In six months, you will have a high degree of autonomy in putting your ideas into practice. This will involve working with our team to define the system architecture, select the appropriate technologies, and implement the solution.

Role Responsibilities

• Design, develop, release and maintain reliable, secure and scalable open-source biometric algorithms (e.g. face recognition)
• Implement reliable, secure, and scalable ML frameworks
• Work cross-functionally with other squads (Android and Backend) in the product and engineering team to design and develop ML products that work for our context
• Use agile software development principles/MLOps practices to build training pipelines and infrastructure together with our Backend team
• Be active in the Best Practice Ambassador community, including senior data scientists & ML engineers