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 environment.
- Other info: Great career growth opportunities in a dynamic and supportive workplace.
- Why this job: Join a passionate team and shape the future of AI with your creativity and intelligence.
- 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 Engineer 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 the flexibility of a hybrid work model in the heart of West London. Recognised as a Great Place to Work, Fractal empowers its employees to challenge possibilities and drive impactful change in the AI landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at Fractal. A personal introduction can make all the difference when it comes to landing that Senior AI Engineer role.
✨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 expertise to potential employers.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with Python, ML libraries, and data pipelines. We want to see how you think and approach challenges!
✨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 setting up email alerts – we’re always looking for passionate individuals to join our team!
We think you need these skills to ace Senior AI Engineer
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 the Senior AI Engineer role. Highlight your experience with model development, data pipelines, and any relevant projects. We love seeing how your skills align with what we do!
Be Clear and Concise:Keep your application clear and to the point. Use bullet points where possible to make it easy for us to read. We appreciate straightforward communication, especially when it comes to your achievements and 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 to do!
How to prepare for a job interview at Fractal Analytics
✨Know Your Models Inside Out
As a Senior AI Engineer, you'll be expected to have a deep understanding of machine learning models. Brush up on your knowledge of recommendation engines, ranking algorithms, and user segmentation. Be ready to discuss specific projects where you've designed, trained, or optimised these models.
✨Showcase Your Data Pipeline Skills
Fractal values robust data pipelines, so make sure you can talk about your experience in constructing and maintaining them. Prepare examples of how you've handled both structured and unstructured datasets, and be ready to discuss the tools and frameworks you've used.
✨Demonstrate Cross-Functional Collaboration
Collaboration is key at Fractal. Think of instances where you've worked with multidisciplinary teams to align machine learning initiatives with business goals. Highlight your communication skills and how you've ensured that technical solutions meet user needs.
✨Stay Updated on Emerging Research
Fractal is all about innovation, so show your passion for staying current in the field. Discuss any recent research in machine learning or generative AI that excites you and how you see it integrating into existing systems. This will demonstrate your commitment to continuous improvement and innovation.
