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For Companies At a Glance
- Tasks: Join a data team to design and deploy AI/ML models for real business challenges.
- Company: Work with a leading fintech organisation in London, known for innovation and growth.
- Benefits: Enjoy hybrid working options and competitive pay based on your experience.
- Why this job: Be part of a dynamic team shaping the future of finance through AI technology.
- Qualifications: Strong Python skills and experience with ML libraries and cloud platforms required.
- Other info: Initial 6-month contract with opportunities for growth in a fast-paced environment.
The predicted salary is between 43200 - 72000 £ per year.
Robert Half Technology are assisting a market leading financial services (fintech) organisation to recruit a AI Engineer on a contract basis – Hybrid working – London based
The AI Engineer will join a cross-functional data team to design, develop, and deploy AI/ML models that tackle real business problems – from prediction and automation to customer personalisation and decision intelligence. You\’ll play a hands-on role in taking models from concept to production and shaping best practices across the AI lifecycle.
Role
- The AI Engineer will build and deploy scalable machine learning models in a cloud-native environment (AWS, GCP or Azure)
- Collaborate with data engineers, analysts, and product teams to translate business needs into AI-driven solutions
- Contribute to the development of data pipelines and feature engineering workflows
- Integrate models into production using APIs, batch jobs, or real-time systems
- Apply best practices around experimentation, evaluation, versioning, and monitoring
- Contribute to documentation, knowledge sharing, and process improvements
Profile
- The AI Engineer will have a proven commercial experience delivering AI/ML projects end-to-end in production environments
- Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face
- Solid understanding of machine learning fundamentals and performance evaluation techniques
- Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI)
- Comfortable working independently and delivering high-quality work to tight timelines
- Experience working in fast-paced environments or scale-up settings
Company
- Market leading financial services (fintech) organisation with offices in London
- Hybrid working – London based
- Initial 6 month contract
Salary & Benefits
The salary range/rates of pay is dependent upon your experience, qualifications or training .
Robert Half Ltd acts as an employment business for temporary positions and an employment agency for permanent positions. Robert Half is committed to diversity, equity and inclusion. Suitable candidates with equivalent qualifications and more or less experience can apply. Rates of pay and salary ranges are dependent upon your experience, qualifications and training. If you wish to apply, please read our Privacy Notice describing how we may process, disclose and store your personal data: roberthalf.com/gb/en/privacy-notice.
AI Engineer employer: Robert Half
Contact Detail:
Robert Half Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Familiarise yourself with the specific AI/ML tools and libraries mentioned in the job description, such as Scikit-learn, TensorFlow, and PyTorch. Having hands-on experience with these will not only boost your confidence but also demonstrate your technical capabilities during discussions.
✨Tip Number 2
Showcase your experience with cloud platforms like AWS, GCP, or Azure by preparing examples of past projects where you deployed machine learning models. Be ready to discuss how you integrated these models into production environments.
✨Tip Number 3
Brush up on your understanding of MLOps tools such as MLflow or SageMaker. Being able to speak about best practices in model versioning, monitoring, and evaluation will set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your approach to collaboration within cross-functional teams. Highlight any experiences where you translated business needs into AI-driven solutions, as this is a key aspect of the role.
We think you need these skills to ace AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI/ML projects, particularly those that demonstrate your ability to take models from concept to production. Include specific examples of your work with Python and relevant libraries like Scikit-learn or TensorFlow.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the fintech industry. Discuss how your skills align with the job requirements, especially your experience in cloud platforms and MLOps tools. Be sure to mention any collaborative projects you've worked on.
Showcase Relevant Projects: If you have a portfolio or GitHub repository, include links to projects that showcase your AI/ML capabilities. Highlight any scalable machine learning models you've built and deployed, as well as your contributions to data pipelines and feature engineering workflows.
Proofread and Edit: Before submitting your application, carefully proofread your documents for any spelling or grammatical errors. Ensure that your application is clear, concise, and free of jargon that may not be understood by all reviewers.
How to prepare for a job interview at Robert Half
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and the ML libraries mentioned in the job description, such as Scikit-learn, TensorFlow, or PyTorch. Bring examples of projects where you've successfully implemented these technologies.
✨Understand the Business Context
Research the fintech industry and understand how AI can solve real business problems. Be ready to discuss how your skills can contribute to customer personalisation and decision intelligence within the company.
✨Demonstrate Collaboration Skills
Since the role involves working with cross-functional teams, prepare to share examples of how you've collaborated with data engineers, analysts, or product teams in the past. Highlight your ability to translate business needs into AI-driven solutions.
✨Familiarise Yourself with Cloud Platforms
Make sure you have a solid understanding of cloud platforms like AWS, GCP, or Azure, and MLOps tools. Be ready to discuss your experience with deploying models in a cloud-native environment and any relevant projects you've worked on.
