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- Tasks: Build and test AI/ML experiments while collaborating with top researchers.
- Company: Join Aeris-UK, a cutting-edge tech company focused on applied AI.
- Benefits: Earn £2,250/month, enjoy weekly lunches, and work in a hybrid model.
- Other info: Flexible start date and excellent career growth opportunities await you.
- Why this job: Dive into real-world AI challenges and make an impact this summer!
- Qualifications: Strong Python skills and practical ML experience required.
The predicted salary is between 27000 - 27000 £ per year.
Aeris-UK is a technology company working on applied AI, modelling and simulation systems.
We are looking for a Summer Applied AI/ML Research Intern to support applied R&D across machine learning, modelling and simulation-related systems. You will work with our ML researchers. This role is suited to strong undergraduate or MSc students with practical ML experience who can contribute from day one while receiving supervision and support.
What You’ll Work On:
- Building and testing AI/ML experiments in Python
- Applying ML methods to practical R&D problems
- Supporting research prototypes and technical investigations
- Analysing results and communicating findings clearly to the team
- Working with modelling, simulation, or system-level environments where relevant
- Improving model, system or simulation performance, scalability or fidelity
Requirements:
- Strong foundation in AI/ML techniques such as deep learning, reinforcement learning or classical ML
- Ability to apply ML methods in practical projects, not only coursework
- Strong Python skills
- Experience with PyTorch and/or TensorFlow
- Solid understanding of data structures, algorithms and computational efficiency
- Strong interest or experience in simulation environments, modelling or system-level thinking
- Strong problem-solving ability and evidence of building real-world projects such as GitHub repositories, research, competitions, demos or substantial coursework
- Comfortable working in a fast-paced R&D environment with some supervision
Strong Plus:
- Numerical methods
- Optimisation techniques
- Probabilistic modelling
- Experience working with or optimising complex simulation systems
- Performance, scalability or fidelity improvements
Bonus Experience:
- Multi-agent systems
- Reinforcement learning
- Large-scale simulation frameworks
Internship Details:
- Duration: 2–3 months
- Start date: negotiable, preference for early summer 2026
- Location: London / hybrid
- Office location: Blackfriars, London
- Working pattern: 40 hours/week
- Team meets in person once per week in London (travel to office paid by company)
- Applicants must have the right to work in the UK
- Compensation: £2,250/month pro rata
- Weekly company-paid lunch and coffee when in the office
How to Apply:
- Please submit: CV
- LinkedIn profile
- GitHub / portfolio / project link
- Right-to-work status
- One sentence describing your strongest relevant project and what you personally built
Applied AI / ML Intern - Summer 2026 in City of London employer: Aeris-UK
Contact Detail:
Aeris-UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI / ML Intern - Summer 2026 in City of London
✨Tip Number 1
Network like a pro! Reach out to current or former interns at Aeris-UK on LinkedIn. Ask them about their experiences and any tips they might have for landing the role. Personal connections can make a huge difference!
✨Tip Number 2
Show off your skills! Make sure your GitHub is up-to-date with your best projects. Highlight any AI/ML experiments you've built, especially those using Python, PyTorch, or TensorFlow. This is your chance to shine!
✨Tip Number 3
Prepare for the interview by brushing up on your problem-solving skills. Be ready to discuss how you've applied ML methods in real-world projects. Practice explaining your thought process clearly and confidently.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team. Don’t forget to include that one-liner about your strongest project!
We think you need these skills to ace Applied AI / ML Intern - Summer 2026 in City of London
Some tips for your application 🫡
Craft a Stellar CV: Your CV is your first impression, so make it count! Highlight your AI/ML skills, relevant projects, and any practical experience you've got. Keep it concise and tailored to the role – we want to see what makes you stand out!
Show Off Your Projects: Don’t forget to include your GitHub or portfolio link! We love seeing real-world applications of your skills. Share your strongest project and explain what you built and how it relates to the role – this is your chance to shine!
LinkedIn Matters: Make sure your LinkedIn profile is up-to-date and reflects your skills and experiences. It’s a great way for us to get a fuller picture of who you are and what you can bring to the table. Plus, it shows you’re serious about your professional presence!
Be Clear and Concise: When writing your application, clarity is key! Make sure to communicate your findings and experiences clearly. We appreciate straightforwardness, so avoid jargon and keep it simple – we want to understand your journey without any confusion!
How to prepare for a job interview at Aeris-UK
✨Know Your Stuff
Make sure you brush up on your AI/ML techniques, especially deep learning and reinforcement learning. Be ready to discuss how you've applied these methods in real-world projects, not just in your coursework.
✨Show Off Your Python Skills
Since you'll be building and testing experiments in Python, be prepared to talk about your experience with it. Bring examples of your work, especially if you've used PyTorch or TensorFlow in your projects.
✨Communicate Clearly
You'll need to analyse results and share findings with the team, so practice explaining complex concepts in simple terms. Think about how you can present your past projects and their outcomes clearly and concisely.
✨Demonstrate Problem-Solving Ability
Be ready to discuss specific challenges you've faced in your projects and how you overcame them. Highlight any experience with optimisation techniques or improving system performance, as this will show your practical skills.