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Open nowPosted 261 days ago

Lead Machine Learning Engineer, AI

Workable (global search)108,016 open roles

Where
Cheltenham, England, United Kingdom
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Your applicationOpen nowLead Machine Learning Engineer, AIWorkable (global search) · Cheltenham, England, United Kingdom
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Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 261 days ago

Workable (global search) median: 7 days open

The posting

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: [email protected]

Nat Hinds: Head of Talent

Kayla Kirby: Talent Acquisition Specialist

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