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 across multidisciplinary teams.
- Why this job: Join a team that empowers imagination with intelligence and drives real-world impact.
- Qualifications: Expertise in machine learning lifecycle, Python proficiency, 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!
Hiring Related Queries:
- India: HiringsupportIndia@fractal.ai
- Outside India: HiringsupportROW@fractal.ai
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Senior AI Engineer in London employer: Fractal
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
Show off your skills! Prepare a portfolio showcasing your machine learning projects, especially those related to personalisation and recommendation systems. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Practice makes perfect! Brush up on your technical skills and be ready for coding challenges or technical interviews. Use platforms like LeetCode or HackerRank to sharpen your problem-solving abilities in Python and ML frameworks.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Fractal team!
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 how your skills align with what we do at Fractal, so don’t hold back!
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 expertise in ML frameworks or algorithms.
Apply Through Our Website:Remember, all applications need to be submitted through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves!
How to prepare for a job interview at Fractal
✨Know Your Models Inside Out
Make sure you can discuss your experience with machine learning models in detail. Be prepared 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 ready 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 shows that you understand the importance of teamwork in achieving great results.
✨Stay Updated on AI Trends
Fractal is all about innovation, so show your passion for the field by discussing recent advancements in machine learning and generative AI. Mention any research papers or projects you've explored that could be relevant to the role, demonstrating your commitment to continuous learning and improvement.
