Lead Machine Learning Engineer, AI

Zaizi
Cheltenham
4 days ago
Create job alert

Work on exciting public sector projects and make a positive difference in people’s lives. At Zaizi, we thrive on solving complex challenges through creative thinking and the latest tools and tech. 

As a Machine Learning Engineer,AI, you’ll be responsible for researching, developing, and testing new AI algorithms, models, and technologies that businesses can use to automate tasks and gain insights from their data. 

Key responsibilities include building complex models, designing and managing MLOps pipelines for CI/CD, monitoring, and model retraining. Mentoring junior members, influencing technical decisions within the team, and handling complex, non-routine problems.

Our work culture is inclusive, modern, friendly, and democratic. We look for bright, positive-thinking individuals with a can-do attitude. Our people enjoy challenging themselves to be the best at what they do – if that sounds like you, you'll fit right in!

Requirements

Role Objectives

These are the expected objectives for this role. We are happy to discuss this further during the interview process with the successful candidate.

  • Model Development & Delivery: Design, build, test, and deploy complex machine learning models, ensuring high standards of quality, performance, and scalabilityDecide what model is most suitable for use in products and services
  • MLOps Pipeline Management: Design and manage robust MLOps pipelines, including continuous integration/continuous delivery (CI/CD), monitoring, and model retraining, to ensure efficient and reliable model deployment and operation
  • Advanced Problem Solving: Act as a technical expert for complex, non-routine technical challenges within machine learning, developing and implementing innovative and effective solutions
  • Customise, optimise, re-train and maintain existing models
  • Deploy models into production, testing and assuring them to ensure they meet performance requirements
  • Work with others to integrate models with existing systems
  • Check that models used in live products and services stay safe, secure and continue to work effectively

Requirements

  • Broad technical expertise in machine learning, demonstrating a deep understanding of various ML algorithms, frameworks, and best practices.
  • Research. Plans and directs and carries out research activities, acting as a subject matter expert in generative AI research.
  • Emerging Technology Monitoring. Systematically discovers and evaluates new generative AI technologies for business relevance, feasibility and relevance within the National Security Domain.
  • Prototyping. Delivers complex, high-risk proofs of concept that test new AI applications.
  • Specialist Advice. Serves as the primary source of expertise for generative AI within the organization.
  • Data Science. Applies a range of data science techniques to support model development.
  • Proven experience in building, deploying, and managing complex machine learning models.

You don’t meet all the requirements?

Studies show that women and black, Asian and minority ethics people are less likely to apply for a job unless they meet every qualification. So if you’re excited about this role but your experience doesn’t align perfectly with the job description, we’d love you to still apply. You might just be the perfect person for this role, or another role here at Zaizi.

We actively welcome applications from people of colour, the LGBTQ+ community, individuals with disabilities, neurodivergent individuals, parents, carers, and those from lower socio-economic backgrounds.

If you need any accommodations to support your specific situation, please feel free to let us know. For candidates who are neurodiverse or have disabilities, we are happy to make any adjustments needed throughout the interview process—just ask!

Security

This role requires eligibility for UK Government Security Clearance. This currently means candidates must have the right to work in the UK without sponsorship and have lived in the UK continuously for the last 5+ years.

Up to £75,000

Benefits

Compensation

  • Competitive Pay: Salaries reviewed annually to ensure they reflect your performance and market value.
  • Loyalty Pension: We invest in your future. Starting at a 5% employer contribution, we increase this by 0.5% every year after your third anniversary, up to a maximum of 8%.
  • Protection: Comprehensive Group Life Assurance for peace of mind.

Purpose & Culture

  • Real Impact: Work on mission-critical projects that secure and improve the UK's digital infrastructure.
  • Autonomy: A culture that empowers you to make decisions, prototype rapidly, and iterate towards success.
  • Service & Community: We support those who serve. 10 paid days for Reservist Military Service.

Work / Life Balance

  • Time Off: 25 days annual leave + Bank Holidays, with the flexibility to Buy/Sell additional days to suit your lifestyle.
  • Giving back: 2 paid volunteering days per year.

Development & Growth

  • Master Your Craft: Fully funded professional certifications (AWS, GCP, Agile, etc.) supported by 5 days paid study leave.
  • Expand Your Horizons: An additional £500 annual "Personal Choice" fund to learn whatever inspires you—work-related or not.
  • Support: Access to 1-2-1 professional coaching and team training to accelerate your career.

Health & Balance

  • Premium Health: Vitality Private Medical Insurance (includes Apple Watch, gym discounts, and rewards).
  • Flexibility: Genuine hybrid working with a WFH equipment allowance to perfect your home setup.
  • Wellbeing: Cycle to Work scheme and a commitment to sustainable, healthy working practices.

For further information contact:

Nat Hinds: Head of Talent

Kayla Kirby: Talent Acquisition Specialist

Related Jobs

View all jobs

Lead Machine Learning Engineer, Gen AI

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

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.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.