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- Tasks: Build and optimise AI workflows, deploy models, and automate processes.
- Company: Join a leading financial services firm in Edinburgh with a collaborative culture.
- Benefits: Competitive salary, hybrid work, and opportunities for personal and professional growth.
- Why this job: Make an impact in AI and machine learning while working with cutting-edge technology.
- Qualifications: Experience in machine learning, Python, Kubernetes, and CI/CD tools.
- Other info: 12-month contract with potential for extension and excellent career development.
The predicted salary is between 30000 - 38000 £ per year.
Location: Edinburgh
Hybrid role: working 2 days a week in the office
Salary: 30,000 to 38,000
Contract: 12-month fixed term contract
Our market-leading financial services client is seeking a motivated, detail-oriented Graduate Machine Learning and AI Engineer to join the Business Transaction Banking division. This role involves building and optimising agent workflows, integrating LLMs with internal tools/data. You will also be involved with model deployment, automation & CI/CD, and deploying artefacts into Kubernetes pods, ensuring scalability, resilience, and proper resource allocation.
Responsibilities
- Model Deployment: Take trained AI/ML models and package them into deployable artefacts (e.g., Docker images).
- Kubernetes Orchestration: Deploy these artefacts into Kubernetes pods, ensuring scalability, resilience, and proper resource allocation.
- Automation & CI/CD: Build pipelines for automated deployment, testing, and monitoring of models.
- Environment Management: Handle containerisation (Docker), networking, and configuration for production environments.
- Monitoring & Logging: Implement tools to track model performance, resource usage, and system health.
Skills and Experience
- Have research or practical experience with machine learning engineering and artificial intelligence
- Experience using Python, Kubernetes, Docker
- Experience using CI/CD tools: Jenkins, GitHub Actions, or Azure DevOps
- Experience using Cloud Platforms: AWS, Azure, or GCP
- Basic Machine Learning Knowledge: Understanding of how models work to troubleshoot deployment issues
- Great attention to detail
- Analytical mindset and uses a methodological approach to complete tasks
- Resilient, confident, professional, and able to work effectively with multiple teams
You will be a valued member of our Adecco Emerging Talent function working onsite with a market-leading organisation. Initially, the assignment is 12 months with scope for extension in the future, so you need to be someone with a permanent mindset.
If you have the experience and desire to work for a well-respected organisation offering personal and professional support, growth and development, then you could be a perfect fit for the team and we want to hear from you - APPLY NOW.
Please be advised if you haven't heard from us within 48 hours then unfortunately your application has not been successful on this occasion; we may however keep your details on file for any suitable future vacancies and contact you accordingly.
Adecco Emerging talent is an employment consultancy and operates as an equal opportunities employer.
Graduate Machine Learning and AI Engineer in London employer: Pontoon
Contact Detail:
Pontoon Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate Machine Learning and AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. 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 practising common technical questions related to ML and AI. Brush up on your Python, Kubernetes, and Docker knowledge, and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to engage with us directly.
We think you need these skills to ace Graduate Machine Learning and AI Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Graduate Machine Learning and AI Engineer role. Highlight relevant skills like Python, Kubernetes, and any experience with CI/CD tools. We want to see how your background fits perfectly with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and AI, and how your experiences align with our needs. Keep it concise but engaging – we love a good story!
Showcase Your Projects: If you've worked on any projects related to AI or ML, make sure to mention them! Whether it's a university project or something personal, we want to see your hands-on experience. Include links if possible – we love seeing your work in action!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts and you’ll be all set!
How to prepare for a job interview at Pontoon
✨Know Your Tech Stack
Make sure you’re familiar with the technologies mentioned in the job description, like Python, Kubernetes, and Docker. Brush up on your knowledge of CI/CD tools like Jenkins or GitHub Actions, as well as cloud platforms such as AWS or Azure. Being able to discuss these confidently will show that you're ready to hit the ground running.
✨Showcase Your Projects
Prepare to talk about any relevant projects you've worked on, especially those involving machine learning or AI. Be ready to explain your role, the challenges you faced, and how you overcame them. This not only demonstrates your technical skills but also your problem-solving abilities.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare some thoughtful questions about the team, the projects you'll be working on, or the company culture. This shows your genuine interest in the role and helps you determine if it’s the right fit for you.
✨Demonstrate Your Analytical Mindset
Since the role requires an analytical approach, be prepared to discuss how you tackle problems methodically. You might even be asked to solve a technical problem on the spot, so practice explaining your thought process clearly and logically.
