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- Tasks: Build and optimise AI workflows, deploy models, and automate processes.
- Company: Join a market-leading financial services firm in Edinburgh.
- Benefits: Competitive salary, hybrid work, and opportunities for growth.
- Why this job: Make an impact in AI while working with cutting-edge technologies.
- Qualifications: Experience in machine learning, Python, Kubernetes, and CI/CD tools.
- Other info: 12-month contract with potential for extension and 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-focused 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. Additionally, you will have the opportunity to be involved with model deployment, automation & CI/CD. You will also be deploying these artefacts into Kubernetes pods, ensuring scalability, resilience, and proper resource allocation.
Key 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.
- Have research or practical experience with machine learning engineering and artificial intelligence.
- Experience using the following: 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 Dunfermline employer: Adecco
Contact Detail:
Adecco Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate Machine Learning and AI Engineer in Dunfermline
✨Tip Number 1
Network like a pro! Reach out to professionals in the machine learning and AI space on LinkedIn. Join relevant groups, attend meetups, and don’t be shy to ask for informational interviews. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, Kubernetes, and Docker. Share it on GitHub or your personal website. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with CI/CD tools and cloud platforms. Practise common interview questions related to machine learning and AI, and don’t forget to highlight your attention to detail!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. Don’t hesitate to follow up after applying; it shows your enthusiasm and commitment!
We think you need these skills to ace Graduate Machine Learning and AI Engineer in Dunfermline
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 machine learning, make sure to mention them! Whether it's a personal project or something from your studies, we want to see your hands-on experience and creativity 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 Adecco
✨Know Your Tech Stack
Make sure you’re well-versed in 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 they might ask you to explain how you've used them in past projects.
✨Showcase Your Projects
Prepare to discuss any relevant projects or experiences where you’ve deployed machine learning models or worked with cloud platforms. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your practical experience and analytical mindset.
✨Ask Insightful Questions
At the end of the interview, don’t shy away from asking questions about the team dynamics, the tools they use, or their approach to model monitoring and logging. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you.
✨Demonstrate Attention to Detail
Since the role requires great attention to detail, be prepared to discuss how you ensure accuracy in your work. You could mention specific strategies you use when coding or deploying models, which will highlight your methodical approach and resilience.
