At a Glance
- Tasks: Design and optimise machine learning models for user personalisation and data pipeline engineering.
- Company: Fractal, a strategic AI partner to Fortune 500 companies, known for its innovative culture.
- Benefits: Hybrid work model, competitive salary, and a vibrant team of enthusiastic over-achievers.
- Other info: Great career growth opportunities in a dynamic and supportive environment.
- Why this job: Join a mission-driven company where your work empowers imagination with intelligence.
- Qualifications: Expertise in machine learning lifecycle, proficiency in Python, and strong problem-solving skills.
The predicted salary is between 60000 - 80000 £ per year.
It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business.
Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.
What you’ll be doing:
- Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis.
- Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets.
- Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance.
- Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.
- Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.
- Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.
What you'll bring:
- Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance.
- Proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch).
- Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (e.g., Tensorflow Serving, Triton, TorchServe).
- Experience with 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.
- Good communication and analytical problem-solving skills.
Good to have:
- Experience working on OTT platforms
- Experience in Scala
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Senior AI Engineer — Personalisation & Production ML employer: Fractal Analytics
Fractal is an exceptional employer that fosters a vibrant work culture where creativity and innovation thrive. With a commitment to employee growth, the company offers numerous opportunities for professional development and collaboration across diverse teams. Located in West London, Fractal provides a hybrid work model that promotes work-life balance while empowering its employees to make impactful contributions in the field of AI.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer — Personalisation & Production ML
✨Tip Number 1
Network like a pro! Reach out to current employees at Fractal on LinkedIn or other platforms. A friendly chat can give you insider info and might just get your application noticed.
✨Tip Number 2
Show off your skills! If you've got a portfolio of projects or GitHub repositories, make sure to highlight them during interviews. We love seeing real-world applications of your expertise!
✨Tip Number 3
Prepare for technical challenges! Brush up on your machine learning concepts and be ready to discuss your past experiences in detail. We want to see how you think and solve problems.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets into the right hands. Plus, it shows you're genuinely interested in joining our team at Fractal.
We think you need these skills to ace Senior AI Engineer — Personalisation & Production ML
Some tips for your application 🫡
Show Your Passion:When you're writing your application, let your enthusiasm for AI and personalisation shine through! We want to see that you truly believe in the power of technology to enhance user experiences.
Tailor Your CV:Make sure your CV is tailored to highlight your experience with machine learning models and data pipelines. We love seeing specific examples of your work that align with what we're looking for!
Be Clear and Concise:Keep your application clear and to the point. We appreciate well-structured applications that make it easy for us to see your skills and experiences without wading through unnecessary fluff.
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 to do!
How to prepare for a job interview at Fractal Analytics
✨Know Your Models Inside Out
Make sure you can discuss your experience with machine learning models in detail. Be ready to explain how you've designed, trained, and optimised models, especially those focused on user personalisation. Use specific examples from your past work to illustrate your expertise.
✨Showcase Your Data Pipeline Skills
Fractal values robust data pipelines, so be prepared to talk about your experience in constructing and maintaining them. Highlight any projects where you’ve worked with large-scale datasets and how you ensured the efficiency of feature engineering and model training.
✨Demonstrate Cross-Functional Collaboration
Since collaboration is key, think of instances where you've worked with multidisciplinary teams. Share how you aligned machine learning initiatives with business objectives and user needs, showcasing your ability to communicate effectively across different functions.
✨Stay Updated on Emerging Trends
Fractal is all about innovation, so show your passion for research in machine learning and personalisation. Discuss any recent advancements or technologies you've explored, particularly in generative AI, and how you see them fitting into production settings.
