Occasional remote work is allowed for this position.
Type of contract for this position: Permanent contract
The position
Job description
As a Senior Applied AI/ML Scientist on the Search team, you will help shape the technical vision, machine-learning algorithm strategy, and system design behind one of our most important growth levers: Search (the primary tool used by customers on any e-commerce site)
You will advance real-time search and recommendation systems that power next-generation shopping experiences
You’ll work at the frontier of algorithms, combining query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for every user query
This is a rare chance to influence the end-to-end personalized discovery experience at Faire within a high-scale, deeply multi-modal environment, while collaborating closely with a talented team of scientists and engineers
Build our next-generation Search ranking algorithms by integrating the latest advances in deep learning and machine learning to personalize the retailer discovery journey at Faire
Leverage LLM to extract multimodal signals (text, visual) to better profile users and their intents
Partner closely with teams across Faire to experiment and improve the ML models for search ranking and beyond
Design and productionize natural-language search and discovery systems so that intelligent agents can generate relevant and personalized collections, explain search results, and assist retailers with browsing, filtering, and evaluation
Share best practices regarding deep learning model development, agent-workflow evaluation, and MLOps, and help teammates level up through code reviews and technical guidance
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.
Preferred experience
5+ years of industry experience building large-scale ML models with business impact and shipping ML solutions to production, including 3+ years in search, recommendation, or ads ranking
Deep understanding of machine learning best practices (e.g., training/serving, imbalanced data, A/B testing, feature engineering, and feature/model selection) and algorithms (e.g., user modeling, deep learning, and reinforcement learning) with applications in search, recommendation, and advertising domains
Excellent written and verbal communication skills and strong cross-functional influence that raise the technical bar beyond your immediate team
A product-focused mindset and a bias toward execution—moving quickly from research papers to prototypes and production
Strong programming skills (Python, Java, or equivalent) and hands-on experience with deep-learning libraries (e.g., PyTorch) and big data technologies (e.g., Spark)
A Master’s or PhD in Computer Science, Statistics, or a related STEM field
Industry experience building search and recommendation systems for e-commerce or two-sided marketplaces
Contributions to open-source ML libraries or peer-reviewed publications in ML/AI
Industry experience developing and productizing LLM-based applications and systems in the search domain
Experience using AI tools (e.g., Cursor, Claude Code, Codex) for code development and daily productivity
Familiarity with Kotlin
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