Machine Learning Engineer
London, Spain
Applications have closed
Teya
Teya offers small and medium businesses reliable card machines and tap-to-pay solutions, ensuring secure and efficient payment processing for every transaction.Company Description
Hello! We're Teya.
Teya is a payment and software service provider, headquartered in London serving small, local businesses across Europe. Founded in 2019, we build easy to use, integrated tools that enable our members to accept payments and boost business performance.
At Teya we believe small, local businesses are the lifeblood of our communities.
We’re here because we don’t believe there’s a level playing field that gives small businesses with a fighting chance against the giants of the high street.
We’re here because we see banks and legacy service providers making things harder for them. We don’t think the best technology or the best service should be reserved for those with the biggest headquarters.
We’re here to fight for a future where small, local businesses can thrive, and to commit the same dedication they offer all of us.
Become a part of our story.
We’re looking for exceptional talent to join our mission. We offer a chance to create impact in a high-energy and connected culture, while benefiting from continuous learning opportunities, a supportive community which is proud to serve our mission, and comprehensive benefits.
Job Description
About the Team
Join a team of machine learning engineers building a real-time decision making platform in Go and Python for fraud detection and mitigation models to protect merchants, their customers, and Teya from fraudulent activities. Working with advanced predictive models and scalable software systems, build and grow intelligent solutions to reduce all kinds of risk and allow Teya to focus on effectively serving our merchants. Key individual contributor for a diverse and innovative team of machine learning engineers to continuously improve and address fast-moving risks and opportunities. Work with senior engineering leaders to design, implement, launch, iterate, and ensure engineering and operational excellence for critical systems with high standards for availability, throughput, and reliability. Collaborate with your peers across Teya to build systems that can integrate real-time decision making wherever opportunity arises.
Your Mission
As a Machine Learning Engineer on the Fraud Prevention team you will:
- Join in the early stage design of a platform for real time decision making including fraud evaluation.
- Build high quality solutions using technologies such as Go, Python, Kafka, Docker, and Kubernetes.
- Work with dedicated Product Managers to deliver scalable platforms and services to build and execute advanced predictive models.
- Help build a culture of quality and delivery.
- Work with best in class tools for observability, monitoring, and analysis.
Qualifications
Your Story
- 2+ years of professional software development experience with machine learning systems.
- Ability to solve problems in code using data structures and algorithms and be able to analyze the time and space complexity of those solutions.
- Understanding of software system design including object-oriented, functional, and distributed design principles.
- Able to work autonomously with little supervision.
Additional Information
The Perks
- We trust you, so we offer flexible working hours, as long it suits both you and your team;
- Physical and mental health support through our partnership with GymPass giving free access to over 1,500 gyms in the UK, 1-1 therapy, meditation sessions, digital fitness and nutrition apps;
- Our company offers extended and improved maternity and paternity leave choices, giving employees more flexibility and support;
- Cycle-to-Work Scheme;
- Health and Life Insurance;
- Pension Scheme;
- 25 days of Annual Leave (+ Bank Holidays);
- Office snacks every day;
- Friendly, comfortable and informal office environment in Central London.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Docker Engineering Kafka Kubernetes Machine Learning Python
Perks/benefits: Career development Fitness / gym Flex hours Health care Parental leave Startup environment Team events
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