Senior Machine Learning Engineer, Checkout.com

• 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

Desirable

• 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
• 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