Top Benefits
Comprehensive healthcare
Offices designed with local in mind
Paid vacation time
About the role
Who you are
- 1-3 years of industry or research experience using machine learning to solve real-world problems, ideally including work in search, recommendations, 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
What the job involves
- As an Applied AI/ML Scientist on the Search Group, you’ll work with world-class machine learning scientists to execute the ML algorithm strategy and system design powering one of the most critical levers for customer value and company growth—Search
- You’ll collaborate on 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 and brands for any given query
- This is a rare opportunity to work on end-to-end Search/Recommendation in a high-scale, deeply multi-modal environment, where we bring together the top talents from companies including Google, Meta, Amazon, LinkedIn, Uber, Airbnb, Salesforce, Twitter, Square, Pinterest, Instacart, and Coupang
- Contribute to 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 <100 ms 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
- Collaborate on model development and GPU-based deployment efforts, leveraging frameworks like Triton to scale inference reliably and efficiently
Benefits
- Comprehensive healthcare
- All of our offices have been designed with local in mind—from our architects to our coffee blends
- Paid vacation time, holidays, and company-wide “Faire Fundays.”
- Including a monthly credit toward your wellness-related programs
- Generous parental and family leave, as well as fertility support benefits
- Including free access to Modern Health therapists and resources
- Optional morning meditation, plus a free Headspace membership
- Faire will match up to US$250 of your charitable donations, every year
- For personal and professional development, as well as unlimited access to training courses through LinkedIn Learning
- 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
Top Benefits
Comprehensive healthcare
Offices designed with local in mind
Paid vacation time
About the role
Who you are
- 1-3 years of industry or research experience using machine learning to solve real-world problems, ideally including work in search, recommendations, 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
What the job involves
- As an Applied AI/ML Scientist on the Search Group, you’ll work with world-class machine learning scientists to execute the ML algorithm strategy and system design powering one of the most critical levers for customer value and company growth—Search
- You’ll collaborate on 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 and brands for any given query
- This is a rare opportunity to work on end-to-end Search/Recommendation in a high-scale, deeply multi-modal environment, where we bring together the top talents from companies including Google, Meta, Amazon, LinkedIn, Uber, Airbnb, Salesforce, Twitter, Square, Pinterest, Instacart, and Coupang
- Contribute to 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 <100 ms 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
- Collaborate on model development and GPU-based deployment efforts, leveraging frameworks like Triton to scale inference reliably and efficiently
Benefits
- Comprehensive healthcare
- All of our offices have been designed with local in mind—from our architects to our coffee blends
- Paid vacation time, holidays, and company-wide “Faire Fundays.”
- Including a monthly credit toward your wellness-related programs
- Generous parental and family leave, as well as fertility support benefits
- Including free access to Modern Health therapists and resources
- Optional morning meditation, plus a free Headspace membership
- Faire will match up to US$250 of your charitable donations, every year
- For personal and professional development, as well as unlimited access to training courses through LinkedIn Learning
- 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