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 workplace recognised as a Great Place to Work.
- Other info: Dynamic environment with opportunities for growth and collaboration with enthusiastic teams.
- Why this job: Join a team that empowers imagination with intelligence and drives impactful AI solutions.
- 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 data.
- 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 in London 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 opportunities for professional development and collaboration across multidisciplinary teams, all while enjoying a hybrid work model in the dynamic setting of West London. Recognised as a Great Place to Work, Fractal empowers its employees to challenge possibilities and contribute meaningfully to cutting-edge AI solutions for Fortune 500 companies.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Fractal on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Senior AI Engineer role. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for technical interviews by brushing up on your machine learning concepts and coding skills. Practice common algorithms and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨Tip Number 3
Showcase your passion for AI! During interviews, share your thoughts on the latest trends in machine learning and how they could apply to Fractal's vision. This will demonstrate your enthusiasm and alignment with our goals.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, you can set up alerts for future opportunities that match your interests. Let’s get you on board!
We think you need these skills to ace Senior AI Engineer in London
Some tips for your application 🫡
Show Your Passion:When you're writing your application, let your enthusiasm for AI and machine learning shine through! We want to see that you truly believe in the power of technology to make a difference.
Tailor Your CV:Make sure your CV is tailored to highlight your experience with model development and data pipelines. We love seeing specific examples of your work, so don’t hold back on the details!
Be Clear and Concise:Keep your application clear and to the point. We appreciate straightforward communication, so avoid jargon unless it’s necessary to showcase your skills.
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!
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 around user personalisation. Bring examples of your work that showcase your expertise in recommendation engines and ranking algorithms.
✨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 specific tools or frameworks you've used, like TFX or Kubeflow, and discuss how you've handled both structured and unstructured data in your previous roles.
✨Demonstrate Cross-Functional Collaboration
Since the role involves working with multidisciplinary teams, share examples of how you've successfully collaborated with others to align machine learning initiatives with business objectives. This could include discussing any A/B tests you've led or how you've communicated complex ideas to non-technical stakeholders.
✨Stay Updated on Emerging Trends
Fractal is all about innovation, so show your passion for research in machine learning and deep learning. Be ready to discuss any recent advancements you've followed and how they could potentially integrate into existing systems. This will demonstrate your commitment to continuous improvement and staying ahead in the field.
