Staff Applied ML/AI Scientist

Who you are

• 7+ years of experience building large-scale ML systems, including 3+ years in search, recommendation, or ads ranking
• Hands-on experience with deep learning libraries (e.g. PyTorch) and vector search infrastructure (e.g. Faiss, ScaNN, Pinecone)
• A strong track record of productionizing models that blend LLMs (e.g. BERT, GPT-class) with structured features to drive personalization
• A product-focused mindset and a bias toward execution—you move quickly from paper to prototype to production
• Strong Python skills, deep respect for system reliability and ownership, and experience operating in high-stakes environments
• Excellent communication and cross-functional influence—you raise the technical bar beyond your immediate team
• Contributions to open-source ML libraries or peer-reviewed publications in ML/AI
• MS or PhD in Computer Science, Statistics, or a related STEM field
• Strong practices around model development, agent workflow evaluation, and MLOps

What the job involves

• As a Staff Applied AI/ML Scientist on the Search Group, you’ll drive the technical vision, ML algorithm strategy, and system design powering one of the most critical levers for customer value and company growth—Search (think about what you do when you land on any e-commerce site)
• You’ll lead the advancement of real-time Search and Recommendation systems behind our next-generation shopping experiences
• You’ll operate at the forefront of algorithms—combining large language models, natural language processing, query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products/brands for any given query from the users
• This is a rare opportunity to own end-to-end personalization in a high-scale, deeply multi-modal environment—while mentoring a team of talented scientists and engineers
• Own the next-generation Search engine, integrating LLMs, query understanding, dense vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning to serve personalized product feeds with <100ms latency
• Design and productionize natural language search and discovery systems, enabling intelligent agents to generate relevant and personalized collections, explain search results, and assist retailers in browsing, filtering, and evaluation
• Lead model development and GPU-based deployment efforts, leveraging frameworks like Triton to scale inference reliably and efficiently
• Mentor and grow senior Applied Scientists and MLEs, and establish best practices around model development, agent workflow evaluation, and MLOps

Benefits

• Comprehensive healthcare: Including Health, Dental, Vision and Disability for all our locations.
• Time off: Paid time off, holidays and company-wide “Faire Fundays”.
• Parental leave: Generous parental and family leave, as well as fertility support benefits.
• Productivity support: Monthly stipends to help cover work from home connectivity needs.
• Annual learning grant: For personal and professional development, as well as unlimited access to training courses through LinkedIn Learning.
• Thoughtfully designed spaces: All of our offices have been designed with local in mind – from our architects to our coffee blends.
• Fitness and well-being benefits: Including monthly credit towards your wellness-related programmes.
• Mental health benefits: Including free access to Modern Health therapists and resources.
• Charitable matching: Faire will match up to £250 of your charity donations, every year.
• Career planning: Whether you want to grow as a leader, hone your craft or explore a new discipline, our career framework allows space for you to explore.