At a Glance
- Tasks: Join us to research and develop machine learning models for impactful public sector projects.
- Company: Zaizi, a forward-thinking tech company dedicated to improving lives through AI.
- Benefits: Competitive salary, generous leave, professional development, and health perks.
- Other info: Inclusive culture welcoming diverse backgrounds and experiences.
- Why this job: Make a real difference while learning from top engineers in a supportive environment.
- Qualifications: Degree in software engineering or related field with a passion for machine learning.
The predicted salary is between 60000 - 80000 £ per year.
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
- 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 ethnic 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
- 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.
Graduate Machine Learning Engineer, AI in Cheltenham employer: Zaizi
Zaizi is an excellent employer for those looking to make a meaningful impact in government services through design. With a strong focus on professional development, competitive pay, and a supportive hybrid work culture, employees are encouraged to grow their skills while collaborating with a talented team. The opportunity to mentor fellow designers further enriches the experience, making Zaizi a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Graduate Machine Learning Engineer, AI in Cheltenham
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Graduate Machine Learning Engineer, AI in Cheltenham
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Zaizi, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Zaizi. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Zaizi
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Zaizi!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.