Lead Machine Learning Engineer, AI

Zaizi Limited; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Loyalty Pension

Group Life Assurance

Job summary

Zaizi Limited is seeking a Lead Machine Learning Engineer to develop and deploy sophisticated ML models for public sector projects. You will lead a team, design MLOps pipelines, and ensure robust, production-ready solutions in a dynamic environment.

The role emphasizes mentoring, architectural influence, and delivering scalable AI solutions while staying current with state-of-the-art AI developments and security requirements.

Qualifications

• Experience with building and deploying ML models.
• Strong knowledge of ML algorithms and frameworks.
• Ability to mentor junior engineers and lead a team.

Responsibilities

• Design, build, test, and deploy complex ML models.
• Design and manage robust MLOps pipelines including CI/CD and monitoring.
• Mentor junior team members and influence technical decisions.
• Deploy models into production and ensure performance and security.
• Collaborate with AI and software engineers to integrate models with systems.

Skills

ML

MLOps

CI/CD

Model deployment

Leadership

Job description

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 Lead Machine Learning Engineer, AI, you’ll be responsible for testing, productionising, and deploying new AI algorithms, models, and technologies that businesses can use to automate tasks and gain insights from their data. You will be responsible for leading a team on projects, understanding the project requirements, how to delegate tasks, and manage time.

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!

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 AI and software engineers to integrate models with existing systems
• Check that models used in live products and services stay safe, secure and continue to work effectively

• Broad technical expertise in machine learning, demonstrating a deep understanding of various ML algorithms, frameworks, and best practices.
• 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.
• Be up to date with new developments and the SOTA in AI, and translate this into productionisable code.
• A solid understanding of data science techniques to support model deployment and metrics
• Proven experience in building, deploying, and managing complex machine learning models.

SC Clearance:

Zaizi works with UK Central Government departments on a range of projects. To be able to work on our customer projects, employees must be Security Cleared to a standard acceptable to our Government customers. Due to this restriction we can currently only recruit candidates who have the right to work in the UK without sponsorship and who have lived in the UK for the last 5+ years continuously.

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: [e-mail]

Nat Hinds: Head of Talent

Kayla Kirby: Talent Acquisition Specialist