At a Glance
- Tasks: Lead the design and development of LLM-based AI solutions to enhance product features.
- Company: Join Checkout.com, a top fintech empowering businesses in the digital economy.
- Benefits: Enjoy a hybrid working model with great snacks and meals at the office.
- Why this job: Be part of an innovative team shaping the future of AI in finance.
- Qualifications: Experience in LLMs, Python, and strong analytical skills required.
- Other info: We value diversity and support your success in a collaborative environment.
The predicted salary is between 43200 - 72000 £ per year.
Checkout.com is one of the most exciting fintechs in the world. Our mission is to enable businesses and their communities to thrive in the digital economy. We’re the strategic payments partner for some of the best known fast-moving brands globally such as Wise, Hut Group, Sony Electronics, Homebase, Henkel, Klarna and many others. Purpose-built with performance and scalability in mind, our flexible cloud-based payments platform helps global enterprises launch new products and create experiences customers love.
As a Senior Machine Learning Engineer specialising in Large Language Models (LLMs), you will play a critical role in harnessing the power of advanced NLP technologies to drive innovation and efficiency across our enterprise. As part of Checkout.com’s AI centre of excellence, you will lead LLM-based solutions' design, development, and deployment, collaborating with cross-functional teams to deliver impactful AI-driven applications.
How you’ll make an impact:
- In collaboration with product managers and engineers, research, scope and validate use cases where LLMs can improve Checkout.com’s product features and business processes.
- Design, develop, and fine-tune LLMs for various applications such as chatbots, virtual assistants, text generation, and more.
- Ensure we have the right processes and tools to curate and preprocess large datasets for training and evaluating LLMs, implement strategies for data augmentation, labeling, and annotation.
- As the technical thought leader, increase the AI fluency in the wider business through supporting training programs and mentoring others.
- Ensure that LLM applications adhere to ethical standards and comply with relevant regulations.
Qualifications:
- Proven track record of developing and deploying LLM-based solutions in an enterprise setting as a senior/staff scientist.
- Proficiency in Python and libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and spaCy.
- Strong understanding of LLM architectures (e.g., GPT, BERT, T5) and experience fine-tuning them for specific tasks.
- Demonstrable experience in utilising different model architectures and training techniques to optimize performance.
- Familiarity with prompt engineering techniques and frameworks like LangChain, LlamaIndex, or DSpy.
- Good understanding of LLM models, including other components like VectorDBs and document loaders.
- Strong analytical and problem-solving skills, with the ability to work with complex datasets and extract meaningful insights.
- Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Strong ability to collaborate and communicate with a large and varied group of stakeholders to embed AI into workflows and product features.
Added bonuses:
- Experience with conversational AI and chatbot development.
- Familiarity with ethical considerations and best practices in AI.
- Previous experience in a mentorship or leadership role within a data science team.
Additional Information:
Hybrid Working Model: All of our offices globally are onsite 3 times per week (Tuesday, Wednesday, and Thursday). We’ve worked towards enabling teams to work collaboratively in the same space, while also being able to partner with colleagues globally. During your days at the office, we offer amazing snacks, breakfast, and lunch options in all of our locations.
We believe in equal opportunities. We work as one team. Wherever you come from. However you identify. And whichever payment method you use. Our clients come from all over the world — and so do we. Hiring hard-working people and giving them a community to thrive in is critical to our success. When you join our team, we’ll empower you to unlock your potential so you can do your best work.
We’d love to hear how you think you could make a difference here with us. We want to set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. We’ll be happy to support you.
Senior Machine Learning Engineer - Generative AI London employer: Checkout Ltd
Contact Detail:
Checkout Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer - Generative AI London
✨Tip Number 1
Familiarise yourself with the latest advancements in Large Language Models (LLMs) and their applications. Being well-versed in current trends will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Engage with the AI community by attending meetups, webinars, or conferences focused on NLP and LLMs. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss specific projects where you've successfully implemented LLM solutions. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will showcase your problem-solving skills.
✨Tip Number 4
Highlight your experience with ethical considerations in AI during discussions. Given the importance of compliance and ethics in AI, demonstrating your awareness of these issues can set you apart from other candidates.
We think you need these skills to ace Senior Machine Learning Engineer - Generative AI London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with LLMs and relevant technologies like Python, TensorFlow, and PyTorch. Use specific examples of projects you've worked on that align with the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your skills can contribute to Checkout.com’s mission. Mention any experience you have in mentoring or leading teams, as this is a key aspect of the role.
Showcase Your Technical Skills: Include a section in your application that details your proficiency with LLM architectures and any relevant frameworks. Be specific about your experience with prompt engineering and data preprocessing techniques.
Demonstrate Problem-Solving Abilities: Provide examples of how you've tackled complex datasets and extracted insights in previous roles. This will showcase your analytical skills and ability to work with cross-functional teams.
How to prepare for a job interview at Checkout Ltd
✨Showcase Your LLM Expertise
Be prepared to discuss your experience with large language models in detail. Highlight specific projects where you've developed or deployed LLM-based solutions, and be ready to explain the architectures you used, such as GPT or BERT.
✨Demonstrate Problem-Solving Skills
During the interview, expect to tackle hypothetical scenarios related to NLP technologies. Use these opportunities to showcase your analytical skills and how you approach complex datasets to extract meaningful insights.
✨Communicate Clearly
Since you'll need to explain technical concepts to non-technical stakeholders, practice articulating your ideas clearly and concisely. Prepare examples of how you've successfully communicated complex information in previous roles.
✨Emphasise Collaboration
Highlight your experience working with cross-functional teams. Discuss how you've collaborated with product managers and engineers to drive innovation and improve product features using AI-driven applications.