Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Machine Learning Engineer

Xcede
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer (One Braham (4140), London, United Kingdom)

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Get AI-powered advice on this job and more exclusive features.

This range is provided by Xcede. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from Xcede

Associate Director – Data & AI Recruitment

Senior Machine Learning Engineer

x2 days a week on UK client site, optional London HQ visits

About the Company

We’re partnering with a specialist AI and data consultancy that designs and deploys bespoke machine learning systems across sectors such as national security, defence, critical infrastructure, and digital public services. Their focus is on delivering safe, production-grade AI solutions that drive real-world outcomes for complex, high-stakes environments.

This is a fast-paced, technically elite environment, ideal for someone who thrives on solving operational challenges, building robust MLOps infrastructure, and leading the delivery of AI systems at scale.

The Role

As a Senior Machine Learning Engineer, you’ll be part of cross-functional delivery teams working on technically complex, high-impact AI projects. You’ll play a central role in designing and building the ML architecture (from infrastructure and deployment to tooling and automation) to ensure that solutions are not only technically sound, but also scalable, maintainable, and secure.

This is a hands-on role with scope for team leadership, stakeholder engagement, and shaping best practices around modern MLOps. You’ll work alongside data scientists, engineers, designers, and product stakeholders often embedded within mission-critical delivery environments.

Key Responsibilities

  • Lead the design and build of production-ready machine learning pipelines and systems
  • Develop infrastructure and tooling to enable deployment, monitoring, and retraining of ML models
  • Work across the full AI delivery lifecycle, from architecture and integration to performance optimisation
  • Collaborate with customers and stakeholders to understand operational constraints and align on solution design
  • Mentor junior engineers and shape internal technical standards for software quality, reliability, and reproducibility
  • Support the continuous improvement of delivery practices, internal tooling, and knowledge sharing across teams

What We’re Looking For

  • Strong software engineering skills, especially in Python.
  • Experience building robust systems for ML applications
  • Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch)
  • Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling
  • Hands-on experience with Docker and Kubernetes in real-world engineering workflows
  • Solid grasp of ML fundamentals: supervised/unsupervised learning, statistical modelling, evaluation
  • A pragmatic approach to engineering capable of balancing speed, risk, and delivery in complex environments
  • Excellent communication and collaboration skills, especially in client-facing settings
  • Prior experience in a fast-paced or start-up environment is highly valued

If this role interests you and you would like to find out more (or find out about other roles), please apply here or contact us via (feel free to include a CV for review).

Seniority level

  • Seniority levelNot Applicable

Employment type

  • Employment typeFull-time

Job function

  • Job functionInformation Technology
  • IndustriesSoftware Development

Referrals increase your chances of interviewing at Xcede by 2x

Sign in to set job alerts for “Machine Learning Engineer” roles.

London, England, United Kingdom 7 months ago

London, England, United Kingdom 5 days ago

London, England, United Kingdom 4 days ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 2 days ago

Graduate Software Engineer – ML Data Platform

London, England, United Kingdom 1 month ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 2 months ago

London, England, United Kingdom 1 month ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 6 days ago

London, England, United Kingdom 6 days ago

London, England, United Kingdom 4 days ago

Research Engineer, ML, AI & Computer Vision

London, England, United Kingdom 2 days ago

London, England, United Kingdom 1 month ago

London, England, United Kingdom 2 days ago

London, England, United Kingdom 3 weeks ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 2 weeks ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#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.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.