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 Graduate Machine Learning Engineer, you’ll start building the skills to research machine learning models and evaluate how they can be applied within our specialist domain, working alongside and learning from a small team who deliver AI capabilities for the UK government. You'll be curious about all flavours of AI from classical ML to the latest generative and adversarial techniques and keen to learn as the field moves. You'll bring a foundation in software engineering from your degree alongside your ML knowledge, and be eager to get hands-on with research, experiment under guidance, and see how new approaches translate into practical capability for our customers. You'll work closely with, and be mentored by, a small, high-performing team of engineers and researchers, contributing ideas and building new skills as you go.
Our work culture is inclusive, modern, friendly, and democratic. We look for bright, positive thinking individuals with a can do attitude and a genuine appetite for learning. Our people enjoy challenging themselves to be the best at what they do, if that sounds like you, you'll fit right in! And the work itself matters: you'll be helping to keep the UK safe.
Requirements
These are the expected objectives for this role. We are happy to discuss this further during the interview process with the successful candidate.
- Model Research & Evaluation: Support research into emerging machine learning models and techniques, and help assess how they could be applied within our specialist domain.
- Applied AI Research: Help turn research into practical proofs of concept, exploring generative, adversarial and other AI approaches.
- Domain Application: Work with the team to build an understanding of our customers' problems and start translating ML capability into solutions that fit their specialist domain.
- Continuous Learning: Keep pace with the fast moving field of AI building knowledge across different model types and techniques and sharing what you learn with the team.
Skills & Experience
- Technical Expertise: Understanding of machine learning algorithms and frameworks with a foundational grounding in software engineering practices, typically gained through a relevant degree, bootcamp or personal projects, plus a genuine curiosity about how ML models work.
- Research Skills: Comfortable reading academic ML papers and keen to develop the skill of translating findings into practical ideas worth testing.
- Technology Implementation: An interest in evaluating new AI technologies, generative, adversarial or otherwise, and how they might be relevant and feasible within the UK Government domain.
- Prototyping: Enjoy building proofs of concept, and keen to learn how research bridges the gap into real-world application.
- Growth Mindset: Keen to learn from the team and build towards becoming a trusted voice on the practical application of AI within the organisation over time.
- Data Science: An interest in applying data science techniques to support model research, evaluation, and refinement.
- Team Fit: A quick learner who's easy to work with, and will slot naturally into a close-knit, high-performing team.
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!
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.
Up to £40,000
Benefits
Compensation
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Competitive Pay: Salaries reviewed annually to ensure they reflect your performance and market value.
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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%.
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Protection: Comprehensive Group Life Assurance for peace of mind.
Purpose & Culture
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Real Impact: Work on mission-critical projects that secure and improve the UK's digital infrastructure.
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Autonomy: A culture that empowers you to make decisions, prototype rapidly, and iterate towards success.
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Service & Community: We support those who serve. 10 paid days for Reservist Military Service.
Work / Life Balance
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Time Off: 25 days annual leave + Bank Holidays, with the flexibility to Buy/Sell additional days to suit your lifestyle.
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Giving back: 2 paid volunteering days per year.
Development & Growth
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Master Your Craft: Fully funded professional certifications (AWS, GCP, Agile, etc.) supported by 5 days paid study leave.
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Expand Your Horizons: An additional £500 annual "Personal Choice" fund to learn whatever inspires you—work-related or not.
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Support: Access to 1-2-1 professional coaching and team training to accelerate your career.
Health & Balance
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Premium Health: Vitality Private Medical Insurance (includes Apple Watch, gym discounts, and rewards).
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Flexibility: Genuine hybrid working with a WFH equipment allowance to perfect your home setup.
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Wellbeing: Cycle to Work scheme and a commitment to sustainable, healthy working practices.
