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, values imagination and diversity.
- Benefits: Hybrid work model, competitive salary, and a culture that celebrates innovation.
- Other info: Dynamic environment with opportunities for growth and collaboration with enthusiastic teams.
- Why this job: Join a team that empowers creativity with intelligence and makes a real 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!
Senior AI / ML 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 numerous opportunities for professional development while promoting a hybrid work model that balances flexibility with collaboration. Located in West London, Fractal not only empowers its employees to challenge the status quo but also celebrates diversity and imagination as key drivers of success.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI / ML 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/ML Engineer role. Personal connections can make a huge difference!
✨Tip Number 2
Show off your skills! Create 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 to the hiring team.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge. Be ready to discuss your experience with Python, ML libraries, and data pipeline engineering. Practising common interview questions can help you feel more confident and articulate.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, keep an eye on future opportunities by creating an account and setting up email alerts. We want to see you succeed!
We think you need these skills to ace Senior AI / ML 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 highlights relevant experience in model development and data pipeline engineering. 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 straightforward and to the point. We appreciate clarity, so make it easy for us to see your qualifications and how they fit the role of Senior AI / ML Engineer.
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 this role involves working with multidisciplinary teams, prepare to share examples of how you've collaborated with others to align machine learning initiatives with business objectives. Discuss any challenges you faced and how you overcame them to achieve successful outcomes.
✨Stay Updated on Emerging Trends
Fractal is all about innovation, so show your passion for the field by discussing recent advancements in machine learning and personalisation. Mention any research papers or projects you've explored and how they could potentially integrate into existing systems. This will demonstrate your commitment to continuous improvement and innovation.
