Machine Learning Engineer

Teya Services Ltd.
London
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer - London

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Teya exists to make sure that every small and growing business in Europe has the opportunity to thrive. We want to become Europe’s go-to software solution for these businesses, simplifying their every day and helping them reconnect with the joy of running their business. Teya was born in 2019 and is home to over 1,000 employees in 15+ countries.We've built a fast-paced, energetic, and innovative environment that is dedicated to bringing the best solutions to customers.

Apply now, read the job details by scrolling down Double check you have the necessary skills before sending an application.About the TeamJoin 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.Job Description

Your MissionAs 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 Story2+ 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 PerksWe 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.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.