At a Glance
- Tasks: Join us to build impactful ML solutions for thousands of customers.
- Company: Contentful, a leading digital experience platform driving the AI revolution.
- Benefits: Stock options, generous paid time off, and personal education budget.
- Why this job: Be at the forefront of AI innovation and make a real difference.
- Qualifications: Experience in ML, cloud services, and a passion for problem-solving.
- Other info: Inclusive culture with opportunities for career growth and well-being support.
The predicted salary is between 43200 - 72000 ÂŁ per year.
Become part of the AI revolution at Contentful where we build real world AI solutions for thousands of active customers. At Contentful you will help imagine, drive, and build ML solutions which produce immediate customer impact by helping them get more done than they ever imagined. We are looking for an excellent machine learning engineer who understands and has experience in this field and current Generative AI trends. If you’re passionate about pushing the boundaries of what’s achievable with ML products on a large scale content management system, we want you on our team.
What to expect?
- Measure and ensure the high-quality output of ML workloads for our enterprise customers.
- Design, build, and measure production software in the Contentful Platform.
- Conduct focused research and testing using tools like Jupyter Notebook.
- Optimize generative AI products for accuracy, speed, and scalability.
- Integrate ML cloud solutions and adapt them to our large-scale use cases.
- Integrate prompt engineering and fine-tuning for customer use cases.
- Develop software that scales to meet the demands of high-load customer workloads.
- Lead design reviews with peers and stakeholders to decide amongst available technologies.
- Drive the ML education in the team and establish a high standard of quality & ownership.
What you need to be successful?
- Proven experience as a technical leader in a product software development environment.
- Proven Track Record in Model Development, including successfully developing and deploying LLM-based models for various NLP tasks in real-world applications with production workloads.
- Proven ability to work backwards from customer needs to deliver ML-based features that meet those needs.
- Ability to organize and prioritize competing workloads.
- Familiarity with distributed systems and cloud services (e.g., AWS, Azure, GCP).
- Solid understanding of machine learning principles.
- Experience with container frameworks such as Docker or Kubernetes.
- Constructive Problem-Solving: As a natural problem-solver, you bring forward ideas that lead to practical solutions and contribute to product growth.
- Up-to-Date on The Latest Updates on LLM Development & Research: From RAGs to Open-Source models over Agent Architectures – you have an inherent drive to stay up-to-date on what is the latest and greatest.
Preferred:
- Background includes machine learning and AI implementation.
- You can translate a research paper into a PoC if the code does not exist.
What’s in it for you?
- Join an ambitious tech company reshaping the way people build digital experiences.
- Full-time employees receive Stock Options for the opportunity to share in the success of our company.
- Fertility and family building benefits, including a lifetime reimbursable wallet to support your growing family.
- We value Work-Life balance and You Time! A generous amount of paid time off, including vacation days, sick days, education days, compassion days for loss, and volunteer days.
- Time off to care for and focus on your growing family.
- Use your personal annual education budget to improve your skills and grow in your career.
- Enjoy a full range of virtual and in-person events, including workshops, guest speakers, and fun team activities, supporting learning and networking exchange beyond the usual work duties.
- An annual wellbeing stipend to care for your physical, financial, or emotional health.
- A monthly communication phone/internet stipend and phone hardware upgrade reimbursement.
- New hire office equipment stipend for hybrid or distributed employees. Get the gear you need to work at your best.
Who are we?
Contentful is a leading digital experience platform that helps modern businesses meet the growing demand for engaging, personalized content at scale. By blending composability with native AI capabilities, Contentful enables dynamic personalization, automated content delivery, and real-time experimentation, powering next-generation digital experiences across brands, regions, and channels for more than 4,200 organizations worldwide. More than 700 people from more than 70 nations contribute their energy and creativity to Contentful, working from hubs in Berlin, Denver, San Francisco, London, New York, and distributed worldwide.
“Everyone is welcome here” is a celebrated component of our culture. At Contentful, we strive to create an inclusive environment that empowers our employees. We believe that our products and services benefit from our diverse backgrounds and experiences, and we are proud to be an equal opportunity employer. All qualified applications will receive consideration for employment without regard to race, color, national origin, religion, sexual orientation, gender, gender identity, age, physical (dis)ability, or length of time spent unemployed. We invite you to apply and join us!
If you need reasonable accommodations at any point during the application or interview process, please let your recruiting coordinator know.
Senior Machine Learning Engineer (f/m/d) in London employer: Contentful GmbH
Contact Detail:
Contentful GmbH Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer (f/m/d) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those that highlight your experience with LLMs and generative AI. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and approach problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Contentful.
We think you need these skills to ace Senior Machine Learning Engineer (f/m/d) in London
Some tips for your application 🫡
Show Your Passion for ML: When writing your application, let your enthusiasm for machine learning shine through! Share specific examples of projects you've worked on and how they relate to the role. We love seeing candidates who are genuinely excited about pushing the boundaries of ML.
Tailor Your CV: Make sure your CV is tailored to highlight your experience with LLM-based models and cloud services. Use keywords from the job description to show that you understand what we're looking for. This helps us see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you're the perfect fit for the team. Be sure to mention your problem-solving skills and any relevant experience with generative AI products. We want to know how you can contribute to our mission!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and it ensures your application goes straight to our recruitment team. Plus, we can't wait to hear from you!
How to prepare for a job interview at Contentful GmbH
✨Know Your ML Stuff
Make sure you brush up on your machine learning principles and recent trends, especially in generative AI. Be ready to discuss your experience with LLM-based models and how you've applied them in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex problems in previous roles. Highlight your constructive problem-solving approach and how it led to practical solutions that benefited your team or product.
✨Familiarise Yourself with the Tools
Get comfortable with tools like Jupyter Notebook, Docker, and Kubernetes. Be ready to discuss how you've used these in past projects, especially in optimising ML workloads for accuracy and scalability.
✨Understand Customer Needs
Be prepared to explain how you've worked backwards from customer needs to deliver ML features. Think of specific instances where your work directly impacted customer satisfaction or improved their experience.