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 make impactful decisions with cutting-edge AI technology.
- Qualifications: Strong experience in ML frameworks, Python proficiency, and 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:
- Strong demonstrated experience using ML Training frameworks (mainly TFX, Kubeflow Pipelines SDK) and Model Serving technologies (e.g., Tensorflow Serving, Triton, TorchServe).
- 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 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 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, we offer opportunities for professional development and collaboration across multidisciplinary teams, all while enjoying the flexibility of a hybrid work model in West London. Recognised as a Great Place to Work, we empower our employees to challenge possibilities and contribute to meaningful projects that impact Fortune 500 companies.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ML Engineer in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Fractal!
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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior ML Engineer at Fractal.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Fractal.
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We think you need these skills to ace Senior ML Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Fractal, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Fractal. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Fractal
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Fractal!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
