National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Machine Learning Engineer

SR2 | Socially Responsible Recruitment | Certified B Corporation
Leeds
5 days ago
Create job alert

Senior AI/ML Engineer

Location:UK Remote

Type:Permanent, Full-time


About the Role

An established tech company is building out its next generation of intelligent software products and is looking for a highly experiencedStaff-level AI/ML Engineerto lead hands-on development of machine learning systems. This is a deeply technical role focused on applied AI, not management or strategy alone.

You’ll work at the intersection of large-scale data processing, generative AI, and cloud infrastructure, contributing directly to the architecture and delivery of smart features across the platform. If you’re passionate about building production-grade AI tools from the ground up, this role offers the opportunity to shape something new in a growing, fast-paced environment.


Key Responsibilities


End-to-End ML Development

  • Own the full lifecycle of machine learning initiatives — from idea to deployment and monitoring.


Hands-On System Design

  • Architect scalable, reliable ML pipelines and APIs, leveraging cloud-native tools and services.


AI Feature Integration

  • Collaborate with engineering and product teams to embed AI-driven functionality into user-facing software.


Technical Leadership

  • Set standards for MLOps, automation, and performance tuning across the engineering team.


Generative AI & LLMs

  • Explore and integrate modern techniques such as large language models and generative architectures.


Mentorship & Collaboration

  • Support peers through code reviews, design discussions, and knowledge sharing.


Scalability & Reliability

  • Solve practical challenges like data quality, explainability, and robust infrastructure for ML.


What You’ll Bring

  • 7+ years of hands-on experience building ML/AI systems in production.
  • 3+ years in a senior technical contributor or team lead role.
  • Advanced Python skills with exposure to common ML frameworks and data libraries.
  • Solid experience working with cloud platforms (ideally AWS) and infrastructure-as-code tools (e.g., Terraform).
  • Understanding of distributed systems, microservices, and modern software architecture.
  • Hands-on experience with LLMs and generative AI models, including tuning and inference.
  • Ability to set up CI/CD pipelines for ML workflows and manage models in a cloud environment.
  • Strong communication and stakeholder engagement skills.
  • A relevant degree in Computer Science, Engineering, or a related field.


Tech Environment

  • Python
  • Java
  • AWS (incl. services for AI/ML)
  • LLM APIs and orchestration tools
  • Terraform, Docker
  • SQL-based databases
  • GitHub Actions and version control tools


Perks & Benefits

  • Competitive compensation
  • 25 days annual leave + bank holidays
  • Flexible remote work policy
  • "Work from anywhere" option (limited days/year)
  • Home office setup budget
  • Enhanced parental leave
  • Pension contribution plan
  • Collaborative and low-ego engineering culture


Important Notes

  • Applicants must be UK-based.
  • Unfortunately, this position is not eligible for visa sponsorship.

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

National AI Awards 2025

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.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.