Lead Machine Learning Engineer, AI

Overview

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.

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!

• Model Development & Delivery:
  Design, build, test, and deploy complex machine learning models, ensuring high standards of quality, performance, and scalability. Decide what model is most suitable for use in products and services.
• MLOps Pipeline Management:
  Design and manage robust MLOps pipelines, including 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.

• 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.

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

• 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, increasing by 0.5% each year after your third anniversary, up to a maximum of 8%.
• Protection:
  Comprehensive Group Life Assurance.

• 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.

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

• Master Your Craft:
  Fully funded professional certifications (AWS, GCP, Agile, etc.) with 5 days paid study leave.
• Expand Your Horizons:
  An additional £500 annual "Personal Choice" fund to learn whatever inspires you.
• Support:
  Access to 1-2-1 professional coaching and team training to accelerate your career.

• Premium Health:
  Vitality Private Medical Insurance (includes Apple Watch, gym discounts, and rewards).
• Flexibility:
  Hybrid working with a WFH equipment allowance.
• 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