Machine Learning Engineer (Applied AI) (100% Remote in EMEA) in Glasgow

Machine Learning Engineer (Applied AI) (100% Remote in EMEA) in Glasgow

Glasgow Full-Time 48000 - 72000 £ / year (est.) No working from home possible
Testlio

At a Glance

  • Tasks: Design and build AI-powered data products using advanced machine learning techniques.
  • Company: Join a female-founded tech company with a strong focus on inclusivity and collaboration.
  • Benefits: Enjoy flexible remote work, competitive salary, stock options, and a $300 annual learning stipend.
  • Other info: Be part of a dynamic team with excellent career growth opportunities in a fully remote setting.
  • Why this job: Shape the future of AI while working with unique datasets and innovative technologies.
  • Qualifications: Advanced degree in a relevant field and 10+ years of machine learning experience required.

The predicted salary is between 48000 - 72000 £ per year.

Testlio’s fully managed crowdsourced testing platform, powered by our proprietary intelligence technology – LeoAI EngineTM, integrates expert, on-demand testers directly into your release process. Ship faster and more confidently with global coverage across 600,000+ devices, 800+ payment methods, 150+ countries, and 100+ languages.

We are hiring a Staff Machine Learning Scientist (Applied AI) to help design, build, and scale Testlio’s next generation of AI-powered data products. You’ll join our product team and will apply advanced machine learning, data science, and statistical methods to transform the rich data from our software testing platform into actionable insights for our customers. Your work will directly influence how global engineering and product teams understand product quality, user experience, and business impact. This is a hands-on, high-impact opportunity to shape the future of AI at Testlio while working in a remote, collaborative, and fast-paced environment.

Why will you love this job?

  • Build from the ground up: You’ll be part of the team shaping Testlio’s new AI product line, creating real-world solutions that customers will use to make smarter product decisions.
  • High-impact data: Our platform generates unique and complex datasets from software testing at scale, giving you access to rich, real-world data to design and deploy meaningful models.
  • Experiment + innovate: You’ll have freedom to test, prototype, and deploy new approaches in NLP, predictive modeling, and data-driven insights.
  • Cross-functional collaboration: You’ll work closely with engineers and customer-facing teams to ensure your models deliver measurable business value.

Why will you love being a part of Testlio?

  • Great Culture: Testlio is a female-founded company, and half our team identifies as women. We’re proud of our inclusive, purpose-driven culture where people genuinely enjoy collaborating.
  • Remote Work: Our culture is built around remote work. We’ve created systems to allow us to successfully work together asynchronously as a fully remote and globally distributed team.
  • Investment in You: Your growth and well-being matter to us. You’ll have flexible paid time off—including national holidays, personal days, and sick days—plus stock options so you can grow with Testlio.
  • Winning Business: Testlio is growing, profitable, and cash-strong. We are leading our industry with exceptional clients who provide us with a high NPS score and a 4.7 rating on G2.

What would your day look like?

  • Partner with engineering leaders to define, design, and deliver AI Data products.
  • Explore and model complex datasets from Testlio’s platform using statistical, ML, and deep learning techniques.
  • Prototype and validate models, then work with engineering to deploy them into production at scale.
  • Research and implement techniques in areas like NLP, anomaly detection, recommendation systems, and predictive analytics.
  • Translate raw outputs into clear, actionable insights that are easy for customers to understand and use.
  • Measure and improve model performance continuously to ensure accuracy, fairness, and scalability.
  • Contribute to building Testlio’s data science practice — influencing standards, tools, and best practices.

What do you need to succeed?

  • Technical Skills: Advanced degree (Master’s or PhD) in Computer Science, Data Science, Statistics, or a related field. 10+ years applying end-to-end machine learning and statistical modeling solutions to real-world problems, ideally in SaaS or data products. Strong Python skills and experience with deep learning frameworks such as PyTorch and TensorFlow. Hands-on experience with NLP, predictive modeling, recommendation systems, anomaly detection, and training ML and deep learning models from scratch. Expertise in data wrangling, feature engineering, and managing large, complex datasets. Knowledge of Large Language Models (LLMs) and Small Language Models (SLMs), including architecture, training, fine-tuning (LoRA, QLoRA, SFT), and deployment strategies. Proven experience designing, building, and maintaining end-to-end ML pipelines and MLOps frameworks, including model training, deployment, monitoring, and lifecycle management. Hands-on experience designing, deploying, and maintaining AI agents, including multi-agent systems, in production with robust APIs and error handling. Proficiency with SQL, data visualization tools, and cloud platforms such as AWS or Azure.
  • Human Skills: Curiosity + creativity. You’re eager to experiment, learn, and push the boundaries of what’s possible with data. Business orientation. You can translate technical outputs into meaningful customer value. Collaborative spirit. You enjoy working across teams to deliver impact. Adaptability. You thrive in fast-changing environments where priorities evolve as we scale. Mentorship mindset. You enjoy sharing knowledge and uplifting teammates. Growth mindset. You continuously refine your craft, stay current with advances in AI/ML, and seek feedback to improve.

What is the application process?

We do our best to bring on individuals who will be excited about their role and have the potential for a great future with Testlio. Since we are 100% distributed, we’d like you to meet with multiple people from our organization to give you an idea of who you would be working with, your role expectations, etc. Our interview process can take about 3 to 4 weeks to complete.

Diversity and Inclusion: Testlio is an equal-opportunity employer deeply committed to creating an inclusive environment for people of all backgrounds and identities. We are female-founded, and 46% of our team members identify as women.

Machine Learning Engineer (Applied AI) (100% Remote in EMEA) in Glasgow employer: Testlio

At Testlio, we pride ourselves on fostering a vibrant and inclusive remote work culture that empowers our employees to thrive. As a female-founded company, we celebrate diversity and provide ample opportunities for personal and professional growth, including flexible paid time off and a dedicated learning stipend. Join us in shaping the future of AI while collaborating with a passionate team committed to delivering exceptional digital experiences.

Testlio

Contact Details:

Testlio Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Machine Learning Engineer (Applied AI) (100% Remote in EMEA) in Glasgow

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We think you need these skills to ace Machine Learning Engineer (Applied AI) (100% Remote in EMEA) in Glasgow

Machine Learning
Statistical Modelling
Deep Learning
Natural Language Processing (NLP)
Predictive Modelling
Recommendation Systems
Anomaly Detection

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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How to prepare for a job interview at Testlio

Brush Up on Your Statistics

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Get Comfortable with Python and R

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Prepare for Case Studies

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