Staff Data Scientist, Applied AI (Hiring Immediately)

Company Description

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. And it's not just what we build that makes us different. It's how.

We empower passionate problem-solvers to collaborate, innovate and do their best work. That's why we're on the Forbes Cloud 100 list and a Great Place to Work accredited company. And we're just getting started. We're building diverse and inclusive teams around the world - because that's how we create even better experiences for our merchants and our partners. And we need your help. Join us to build the digital economy of tomorrow.

Job Description

As a Staff Data Scientist 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:

1. 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.
2. Design, develop, and fine-tune LLMs for various applications such as chatbots, virtual assistants, text generation, and more.
3. 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.
4. As the technical thought leader, increase the AI fluency in the wider business through supporting training programs and mentoring others.
5. Ensure that LLM applications adhere to ethical standards and comply with relevant regulations.

Qualifications

1. Proven track record of developing and deploying LLM-based solutions in an enterprise setting as a senior/staff scientist.
2. 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.
3. Demonstrable experience in utilising different model architectures and training techniques to optimize performance.
4. 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.
5. Strong analytical and problem-solving skills, with the ability to work with complex datasets and extract meaningful insights.
6. Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
7. Strong ability to collaborate and communicate with a large and varied group of stakeholders to embed AI into workflows and product features.

Nice to have:

1. Experience with conversational AI and chatbot development.
2. Familiarity with ethical considerations and best practices in AI.
3. Previous experience in a mentorship or leadership role within a data science team.

Additional Information

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.

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