AI Engineer / Machine Learning Engineer

Tenth Revolution Group; Greater London; Hybrid; GBP 85,000 - 100,000; Full time

Benefits offered by this job

End-to-end ownership

Impactful work

Shape AI capability

Collaborative environment

Flexible working

Job summary

Tenth Revolution Group in London is seeking an AI Engineer / Machine Learning Engineer to apply and deploy AI/ML solutions in production, with autonomy and ownership. You will design, develop and deploy production-grade Python backends, build cloud-native apps on AWS, and manage data pipelines and ML workflows.

Join a small, high-performing team where ideas matter and delivery is prioritized. This hybrid role offers significant impact across the business and opportunities to shape the company’s

Qualifications

• Commercial experience in ML or Data Science or backend engineering.
• Experience deploying production AI/ML solutions.
• Strong Python and cloud platform experience (AWS).

Responsibilities

• Designing, building and deploying AI/ML solutions into production environments.
• Developing scalable backend applications, APIs and services using Python.
• Building cloud-native solutions within AWS environments.
• Creating and maintaining data pipelines and machine learning workflows.
• Monitoring, testing and optimising AI systems in production.
• Collaborating closely with engineering, product and data teams.
• Working across the full development lifecycle from design through to deployment and support.

Skills

Machine Learning / Data Science

Backend Engineering

Python development

AWS / Cloud

Tools

Docker

Databricks

AWS

Job description

AI Engineer / Machine Learning Engineer

Hybrid (London) - Python - AWS - Databricks - Up to £100,000

We're partnered with an innovative, technology-led organisation that is investing heavily in AI and machine learning as a core part of its future growth. They're looking for an AI Engineer / Machine Learning Engineer to join a small, highly capable team where you'll have the autonomy, ownership and influence that's often missing in larger businesses.

This isn't a research-focused role. It's about applying AI and machine learning to real business challenges, building production-ready solutions and owning projects from initial concept through to deployment and iteration.

You'll be joining a close-knit engineering environment where your ideas will be heard, technical decisions won't get lost in layers of management and you'll have the opportunity to make a meaningful impact across the business. If you enjoy solving complex problems, working with modern technologies and taking ownership of what you build, this could be the role for you.

You Will Work With

• Designing, building and deploying AI/ML solutions into production environments.
• Developing scalable backend applications, APIs and services using Python.
• Building cloud-native solutions within AWS environments.
• Creating and maintaining data pipelines and machine learning workflows.
• Monitoring, testing and optimising AI systems in production.
• Collaborating closely with engineering, product and data teams.
• Working across the full development lifecycle from design through to deployment and support.

Benefits

• Join a small team where your contributions have a direct impact
• End-to-end ownership from design through to production
• Opportunity to shape the future AI capability of the business
• Work across the full AI/ML lifecycle rather than specialising in one area
• Work alongside experienced engineers in a highly collaborative environment
• Clear progression opportunities as the function continues to grow
• Flexible working environment focused on outcomes rather than micromanagement

Key Experience

• Strong commercial experience in either Machine Learning / Data Science or Backend Engineering
• Demonstrable overlap between software engineering and machine learning
• Excellent Python development skills.
• Experience deploying solutions into production rather than purely building models or conducting research
• Exposure to cloud platforms, ideally AWS.
• Docker and containerisation experience
• Knowledge of Databricks, MLOps or modern AI tooling would be beneficial
• Strong engineering fundamentals and a passion for building high-quality solutions.
• Comfortable working in an environment with high responsibility and high expectations.