Machine Learning Engineer - Remote

Simprints is a nonprofit tech company dedicated to radically increasing transparency and effectiveness in worldwide development. We leverage ethical, inclusive digital identification powered by biometrics to ensure that health, aid, and social services effectively reach those in need. Partnering with organizations like Gavi, we boost immunization rates in developing countries, cooperate with Health Ministries like Ghana's for pandemic response, and join forces with NGOs like BRAC in providing maternal healthcare. Studies indicate that Simprints substantially amplifies the impact through real-time, precise data — such as enhancing maternal health visits by 38% in Bangladesh or accurate HIV tracing by 62% in Malawi. We've been active in over 17 countries so far, aiding the delivery of health, financial assistance, and other forms of aid to more than 2.5 million people. We aspire to revolutionize the way poverty is addressed globally, ensuring that every resource, every dollar, and every public good reaches those who desperately need them. About the Role As a Machine Learning engineer, you will join a remote-first agile team overseeing the entire pipeline of our Machine Learning models in biometrics. This includes designing, developing, and deploying machine learning models. You will become an expert in the field, influencing the course of Simprints' development. The role requires you to collaborate with data scientists and engineers to conceptualize and implement machine-learning solutions to real-world problems in tandem with product managers to establish requirements and innovate solutions to the most intricate challenges. This role is remote. However, we're currently only considering applicants located in the UK, Bulgaria, Romania, Hungary, Poland, Croatia, Ukraine, Latvia, Spain, Netherlands, and Germany. The candidates must have permission to work in one of these countries. We cannot provide support for relocation or visa sponsorship. UK Grade 6 Salary: £55,000 - £75,000 with a cost-of-living adjustment for non-UK residents Your Impact At Simprints, we encourage each employee to take ownership of their tasks. As a Senior Machine Learning Engineer, you'll be given a measurable goal or Key Performance Indicator, and you'll be tasked with devising a strategy to achieve this goal. You'll be provided with resources to familiarize yourself with the Simprints biometrics platform and work with other team members to gain a comprehensive understanding of the company and our goals. Role Responsibilities Your duties will include designing, developing, releasing, and maintaining reliable, secure, and scalable open-source biometric algorithms like face recognition, implementing reliable, secure, and scalable ML frameworks, working with other squads in the product and engineering team to design and develop ML products that suit our context, and using agile software development principles/MLOps practices to build training pipelines and infrastructure in conjunction with the Backend team. Requirements This role requires someone with a deep understanding of Computer Vision and other ML areas, algorithms and frameworks, and solid understanding of the full software development lifecycle. To be considered for this role, you need a Ph.D. in Computer Science/Engineering and experience working in a team where testing, code reviews, and continuous integration are the norm. Advantages would include experience applying machine learning in a domain-specific area; experience with agile tools such as JIRA, Confluence; an interest in or experience contributing to open-source projects; and experience deploying machine learning models into the cloud (e.g., GCP). Benefits Our aim is for work to be enjoyable and meaningful at Simprints. Join us, and not only will you grow, but you'll also take on responsibilities that have the potential to significantly impact countless lives. Among our benefits are: - Genuine Impact - work directly influencing millions of lives - Incredible, diverse team - join a globally recognized Great Place to Work and 2022 Best Workplace for Women - Career Advancement - access top players in the field - Flexible hours - outside of core hours, work becomes more flexible - Professional development and well-being - grow with a learning budget, global expert access, and regular feedback - Unlimited paid time off - we trust you to get the job done - 4 day work-week - enjoy a long weekend, every weekend. We are currently on a 6-month pilot testing a 4-day work-week with no expectation of working on Fridays. Initial data indicates this a positive change that we hope to make permanent once the pilot concludes.