At a Glance
- Tasks: Design and optimise machine-learning models for user personalisation and deploy them in production.
- Company: Join a leading tech firm in West London with a hybrid work model.
- Benefits: Enjoy a competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and explore the latest in AI research.
- Why this job: Make a real impact by working on cutting-edge AI projects that shape user experiences.
- Qualifications: Experience in the full ML lifecycle and proficiency in Python required.
The predicted salary is between 60000 - 80000 £ per year.
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 Data Privacy & BigID Consultant, you will thrive in a dynamic work environment that prioritises innovation and collaboration. Our company offers competitive benefits, a strong commitment to employee development, and a culture that values diversity and inclusion, all set against the backdrop of cutting-edge cloud technologies. Join us to advance your career while making a meaningful impact in data privacy across various industries.
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 your connections in the AI and ML space. Attend meetups, webinars, or even local tech events. 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 machine-learning projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your experience with Python, TensorFlow, and other relevant tools. Practice common interview questions and think about how your past projects align with the role.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications come directly from candidates who are genuinely interested in joining our team. Plus, it gives you a better chance to stand out!
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 interesting projects, especially those involving A/B testing or real-time data processing, make sure to include them. We love seeing practical applications of your skills, so don’t hold back!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it’s super easy!
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 they achieved. This shows your depth of knowledge and experience.
✨Showcase Your Data Pipeline Skills
Prepare to talk about your experience with data pipelines. Highlight specific projects where you constructed or maintained robust pipelines for feature engineering and model training. Mention any challenges you faced and how you overcame them.
✨Demonstrate Collaboration
Since collaboration is key, think of examples where you worked with multidisciplinary teams. Be ready to discuss how you aligned machine-learning initiatives with business objectives and user needs, showcasing your ability to communicate effectively.
✨Stay Updated on Trends
Familiarise yourself with the latest trends in AI and ML, especially around personalisation and recommendation systems. Being able to discuss emerging research and its potential applications will impress interviewers and show your passion for the field.
