At a Glance
- Tasks: Design and optimise machine-learning models for user personalisation and deploy them in production.
- Company: Leading tech firm in West London with a focus on innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on cutting-edge research and development.
- Why this job: Join a dynamic team and shape the future of AI technology.
- Qualifications: Experience in machine learning lifecycle and proficiency in Python required.
The predicted salary is between 60000 - 80000 £ per year.
Senior AI / ML Engineer – 12‑month Fixed‑Term Contract, West London. Hybrid work model: onsite 2 days per week.
Responsibilities
- Design, train and optimise machine‑learning models focused on user personalisation, including recommendation engines, ranking algorithms, user segmentation and content analysis.
- Construct and maintain robust, scalable data pipelines for feature engineering and model training, handling both structured and unstructured large‑scale datasets.
- Deploy and supervise ML models in production, ensuring high availability, optimal performance and continued relevance.
- Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.
- Collaborate with multidisciplinary teams to align machine‑learning initiatives with business objectives and user needs.
- Evaluate emerging research in machine learning, deep learning and personalisation for potential integration within existing systems.
Qualifications
- Demonstrated experience across the full machine‑learning lifecycle: model development, deployment, serving, monitoring and maintenance.
- Proficiency in Python and familiarity with ML libraries/frameworks such as TensorFlow and PyTorch.
- Experience with ML training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and model‑serving technologies (e.g., TensorFlow Serving, Triton, TorchServe).
- Knowledge of high‑volume data processing and real‑time streaming architectures.
- Strong understanding of recommendation‑system design and personalisation algorithms.
- Familiarity with Generative AI and its applications in production settings.
- Excellent communication and analytical problem‑solving skills.
- Preferred: experience working on OTT platforms; experience in Scala.
Location & Contract
West London – Hybrid. 12‑month Fixed‑Term Contract.
Senior AI Engineer employer: Fractal Analytics UK Limited
As a Senior AI Engineer at our West London office, you will thrive in a dynamic and innovative work culture that prioritises collaboration and continuous learning. We offer a hybrid work model that promotes work-life balance, alongside opportunities for professional growth through engaging projects and access to cutting-edge technologies. Join us to be part of a forward-thinking team that values your contributions and supports your career development in the exciting field of machine learning.
Contact Details:
Fractal Analytics UK Limited Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML space, especially those who work at companies you're interested in. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine-learning projects, especially those involving recommendation engines or user personalisation. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with Python, TensorFlow, and any cool projects you've worked on.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us. Plus, it makes the process smoother for everyone involved.
We think you need these skills to ace Senior AI Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior AI Engineer role. Highlight your experience with machine learning models, data pipelines, and any relevant projects that showcase your skills in Python and ML frameworks like TensorFlow or PyTorch.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with our mission at StudySmarter. Don’t forget to mention any experience with recommendation systems or personalisation algorithms.
Showcase Your Projects:If you've worked on any cool projects related to AI or machine learning, make sure to include them! Whether it's a personal project or something from a previous job, we love seeing practical applications of your skills.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status directly!
How to prepare for a job interview at Fractal Analytics UK Limited
✨Know Your Models Inside Out
Make sure you can discuss the machine-learning models you've worked on in detail. Be ready to explain your design choices, how you optimised them, and the results you achieved. This shows your depth of knowledge and experience in the full ML lifecycle.
✨Showcase Your Technical Skills
Brush up on your Python skills and be prepared to talk about the ML libraries and frameworks you’ve used, like TensorFlow and PyTorch. If you have experience with ML training frameworks or model-serving technologies, highlight that too. Practical examples will make your expertise stand out.
✨Demonstrate Collaboration
Since this role involves working with multidisciplinary teams, think of examples where you successfully collaborated with others. Discuss how you aligned machine-learning initiatives with business objectives and user needs, as this will show your ability to work effectively in a team environment.
✨Stay Updated on Trends
Familiarise yourself with the latest research in machine learning and personalisation. Be ready to discuss how emerging trends, like Generative AI, could be integrated into existing systems. This shows your passion for the field and your commitment to continuous improvement.
