Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deploy AI models in a dynamic SaaS environment.
- Company: Fast-growing SaaS company with a supportive engineering culture.
- Benefits: Competitive salary, clear progression, and support for learning.
- Why this job: Work on real-world AI systems and make an impact from day one.
- Qualifications: Master’s degree in relevant field and experience with Python and ML libraries.
- Other info: Hybrid role with strong mentoring and collaborative team spirit.
The predicted salary is between 28800 - 43200 £ per year.
We’re looking for a curious and ambitious Graduate AI Engineer to join our growing SaaS team based in Northampton. This is an excellent opportunity for a recent postgraduate to work hands-on with real-world AI and machine learning systems, contributing directly to intelligent, scalable software used by customers every day.
You’ll work closely with experienced engineers, data scientists, and product teams to design, build, and deploy AI-driven features across our platform — from experimentation through to production.
Key Responsibilities- Design, develop, and deploy machine learning and AI models within a SaaS environment
- Work with structured and unstructured data to build predictive and intelligent features
- Collaborate with software engineers to integrate models into production systems
- Evaluate, test, and improve model performance over time
- Contribute to data pipelines, model training workflows, and MLOps practices
- Stay up to date with the latest developments in AI, ML, and data science
- Document models, experiments, and technical decisions clearly
- Master’s degree or higher in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related field
- Strong foundations in machine learning, algorithms, and statistics
- Experience with Python and common ML libraries (e.g. TensorFlow, PyTorch, scikit-learn)
- Understanding of software engineering fundamentals and version control (e.g. Git)
- Ability to communicate technical ideas clearly to both technical and non-technical stakeholders
- Right to work in the UK
- Experience with cloud platforms (AWS, Azure, or GCP)
- Familiarity with data engineering tools or SQL
- Exposure to deploying models into production or MLOps concepts
- Internship, research, or project experience in applied AI
- Hybrid role: a mix of office-based work in Northampton and remote working
- Collaborative, supportive engineering culture with strong mentoring
- Competitive graduate salary
- Clear progression and learning pathway
- Opportunity to work on real production AI systems from day one
- Support for continued learning, conferences, and certifications
- Modern tech stack and a fast-growing SaaS environment
Jr AI Engineer in Kettering employer: Intellect Group
Contact Detail:
Intellect Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Jr AI Engineer in Kettering
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow AI enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and AI. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and coding challenges related to AI and machine learning. Practising with friends or using online platforms can help you feel more confident when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals like you. Tailor your application to highlight your relevant experience and enthusiasm for AI – it’ll make a world of difference!
We think you need these skills to ace Jr AI Engineer in Kettering
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of a Graduate AI Engineer. Highlight your relevant skills, projects, and experiences that align with our job description. We want to see how your background fits into our SaaS environment!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to express your passion for AI and machine learning, and explain why you’re excited about joining our team. Let us know what makes you a great fit for StudySmarter.
Showcase Your Projects: If you've worked on any AI or machine learning projects, make sure to mention them! Whether it's coursework, internships, or personal projects, we love seeing practical applications of your skills. Share links or descriptions to give us a taste of your work.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at Intellect Group
✨Know Your AI Stuff
Make sure you brush up on your machine learning fundamentals and the specific libraries mentioned in the job description, like TensorFlow and PyTorch. Be ready to discuss your experience with these tools and how you've applied them in real-world scenarios.
✨Show Your Curiosity
As a Graduate AI Engineer, they’ll want to see your passion for AI and machine learning. Prepare some questions about the latest trends in the field or recent projects the company has worked on. This shows you’re not just interested in the role, but also in the industry as a whole.
✨Communicate Clearly
You’ll need to explain complex technical concepts to both technical and non-technical stakeholders. Practice articulating your thoughts clearly and concisely. Consider doing mock interviews with friends or mentors to refine your communication skills.
✨Be Ready to Collaborate
Since the role involves working closely with software engineers and product teams, think of examples from your past experiences where you successfully collaborated on projects. Highlight your teamwork skills and how you can contribute to a supportive engineering culture.
