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- Tasks: Develop and deploy cutting-edge AI solutions for major financial clients.
- Company: Join a global consulting firm leading in AI engineering.
- Benefits: Attractive salary, flexible work options, and career growth opportunities.
- Why this job: Be at the forefront of AI innovation in the financial sector.
- Qualifications: Experience in AI, machine learning, or data engineering preferred.
- Other info: Collaborative environment with diverse projects and technologies.
The predicted salary is between 28800 - 48000 £ per year.
Applications are welcome from AI engineers at all levels, from early-career through to experienced professionals.
We're supporting a global consulting firm expanding its AI engineering capability within financial services. Building teams delivering enterprise AI platforms, machine learning systems, and generative AI solutions for banks, insurers, and capital markets organisations.
The role involves working within the engineering team building AI solutions for large enterprise clients. Typical work includes:
- Developing and deploying machine learning models
- Building scalable AI and data pipelines
- Engineering ML systems on modern cloud platforms
- Working with architects and data engineers on enterprise AI platforms
Technology:
- Python
- SQL
- Spark / PySpark
- TensorFlow, PyTorch or similar frameworks
- AWS, Azure or GCP
- Databricks or Snowflake
- Exposure to GenAI or LLMs
We're interested in engineers with experience in:
- AI or machine learning engineering
- Data engineering with ML exposure
- Applied data science with production deployment
- Financial services and consulting experience is preferred, particularly across banking, capital markets, or insurance environments.
If you'd like to hear more, please get in touch. Apply now or email direct Lauren Jones at Lauren.Jones@datatech.org.uk.
AI Engineer - All Seniorities employer: Datatech Analytics
Contact Detail:
Datatech Analytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer - All Seniorities
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with AI engineers 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 AI projects, especially those involving machine learning models or data pipelines. 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 your technical knowledge and problem-solving skills. Practice common AI engineering questions and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented AI engineers at all levels. Your next big opportunity could be just a click away, so get your application in!
We think you need these skills to ace AI Engineer - All Seniorities
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your work with AI, machine learning, and any relevant financial services experience to catch our eye!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI engineering and how your background makes you a great fit for our team. Keep it engaging and personal.
Showcase Your Projects: If you've worked on any cool AI projects or have experience with tools like TensorFlow or AWS, make sure to mention them! We love seeing real-world applications of your skills.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Datatech Analytics
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, SQL, and TensorFlow. Brush up on your knowledge of cloud platforms like AWS or Azure, as they might ask you to explain how you've used these tools in past projects.
✨Showcase Your Projects
Prepare to discuss specific projects where you've developed or deployed machine learning models. Be ready to explain your role, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Understand Financial Services
Since the role is within financial services, it’s crucial to have a grasp of the industry. Familiarise yourself with how AI is transforming banking, insurance, and capital markets. This knowledge will help you connect your technical skills to real-world applications during the interview.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s AI initiatives and future projects. This shows your genuine interest in the role and helps you assess if the company aligns with your career goals. Plus, it gives you a chance to engage with the interviewers on a deeper level.