Lead Machine Learning Engineer, AI

Meraki IT Recruitment
London
2 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer (Forward Deployed)

Senior Machine Learning Engineer

Lead Data Scientist - Remote

Lead Data Scientist - Remote

Senior Data Scientist

Senior Data Scientist

Job Summary


Overview

Work on impactful public sector and mission-critical digital projects that make a positive difference to people’s lives. This organisation specialises in solving complex technical challenges using modern tools, emerging technologies, and innovative thinking.


As a Machine Learning Engineer (AI), you will research, develop, and test advanced AI algorithms, models, and technologies that enable organisations to automate processes and extract meaningful insights from data.


You will build complex machine learning models, design and manage MLOps pipelines, and ensure models remain performant, secure, and scalable in production environments. The role also includes mentoring junior team members, influencing technical decisions, and solving complex, non-routine technical problems.


The culture is inclusive, collaborative, and innovation-driven. The organisation values proactive, positive-thinking individuals who enjoy tackling technical challenges.


Role Objectives

Model Development and Delivery

Design, build, test, and deploy complex machine learning models.

Select appropriate modelling approaches for product and service use cases.

Ensure models meet performance, scalability, and quality standards.


MLOps and Deployment

Design and manage robust MLOps pipelines, including CI/CD processes.

Implement monitoring, retraining, and lifecycle management.

Deploy models into production environments and validate performance.

Ensure models remain safe, secure, and effective in live systems.


Advanced Technical Problem Solving

Act as a subject matter expert for complex, non-routine machine learning challenges.

Develop innovative solutions to high-risk or ambiguous problems.

Customise, optimise, retrain, and maintain existing models.


Integration and Collaboration

Work cross-functionally to integrate machine learning models into existing systems.

Collaborate with engineers, data scientists, and technical stakeholders.

Ensure production systems meet reliability and security standards.


Requirements


Broad expertise in machine learning algorithms, frameworks, and best practices.

Experience planning and conducting research activities within AI or generative AI domains.

Ability to evaluate emerging AI technologies for business relevance and feasibility.

Experience delivering complex proofs of concept and experimental prototypes.

Recognised technical authority within AI or generative AI.

Strong data science capability supporting model development.

Proven experience building, deploying, and managing complex machine learning systems.


Inclusion Statement.


Candidates are encouraged to apply even if they do not meet every requirement. The organisation values diversity and welcomes applications from individuals across all backgrounds, including underrepresented communities.


Reasonable adjustments can be made throughout the recruitment process to support individual needs.


Security RequirementsThis role requires eligibility for government-level security clearance. Candidates must have the legal right to work in the UK without sponsorship and meet residency requirements for clearance eligibility.


Benefits

Competitive salary reviewed annually.

Employer pension contribution starting at 5 percent, increasing with tenure.

Group Life Assurance.

25 days annual leave plus bank holidays, with option to buy or sell leave.

Two paid volunteering days per year.

Fully funded professional certifications and paid study leave.

Annual personal development allowance.

Access to coaching and professional training.

Private medical insurance.

Hybrid working with home office allowance.

Cycle to Work scheme.



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.

Where to Advertise AI Jobs in the UK (2026 Guide)

Advertising AI jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly informed and in demand across multiple sectors simultaneously. General job boards reach a broad audience but lack the specificity that AI professionals expect — and the filtering mechanisms they rely on. Specialist platforms, direct outreach and academic channels each serve a different part of the market. This guide, published by ArtificialIntelligenceJobs.co.uk, covers where to advertise AI roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about time-to-hire across different role types.

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.