Simprints
Machine Learning Engineer - Remote
- Full-time
- $50k-$75k/mo
- 10 months ago
- 301 views
Machine Learning
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.
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.
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
Requirements
What are the “must-have” skills and experience for this role?
- A passionate problem solver who can help us find a way to achieve our mission
- PhD in Computer Science/Engineering
- Deep understanding of Computer Vision and other ML areas, algorithms and frameworks
- Solid understanding of the full software development lifecycle, including application architecture design
- Experience working within a team with a focus on code quality, where testing, code reviews, and continuous integration are the norm
What are the "nice to have" skills and experience for this role?
- History of applying machine learning to a domain-specific area, desirably in biometrics
- Working remotely with modern agile tools such as JIRA, Confluence
- Interest or has worked in contributing to open source projects
- Experience deploying machine learning models into the cloud (e.g. GCP)
Benefits
7 Reasons to join Simprints
Life is short. We believe work should be awesome, meaningful, and fun. At Simprints, we’re taking on global development’s biggest challenges, powered by an amazing culture and incredible people. Work with us, and you will grow faster, learn more, and take on great responsibilities with the potential to make lasting change.
- Genuine Impact. Work directly with our partners and users to deliver technology that has the potential to impact millions of lives.
- Incredible, diverse team. Ask any “Simployee” what their favorite thing about working at Simprints is, and the answer is likely to be “the people.” Our work is at the intersection of technology and global development, and we’ve managed to build an amazing team drawn from all over the world. But don’t take our word for it—we’re an externally recognized
and* Career Advancement. Join the team of a forward-thinking social enterprise that is making waves with some of the biggest names in our sector. Simprints Alumni have gone on to work for Google, USAID, Gavi the vaccine alliance, Save the Children, and other top players.
- Flexible hours. More efficient late at night? Better before the sun rises? Need to squeeze in a doctor’s visit Thursday morning? That’s fine by us. We are looking for people who get the job done, not for people who clock-in and clock-out. Outside of core hours (10am to 3pm UK) it's up to you to decide when the job gets done.
- Professional development and well-being. We promote continual learning with self-directed learning objectives, external mentors, and regular one-on-one feedback. We also put our money where our mouth is with a dedicated ‘Learning ’ budget, and access to global experts through the
- .
- Unlimited paid time off. We set high standards and goals, but give people the freedom to choose when and how to recharge. Join a team that trusts you with the job.
- 4 day work-week. We are currently on a 6 month pilot where we are trialling a 4 day work-week. Nobody is expected to work Friday's, so you'll get to enjoy a long weekend, every weekend. So far, the data has indicated this is a positive change, so we hope to make this a permanent fixture at the end of the pilot.
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