Senior Applied AI/ML Scientist - Search Ranking
About this role
Faire needs to improve search ranking algorithms to connect independent retailers with global products, solving the fragmentation in the wholesale market. The Search team builds real-time search and recommendation systems that serve as a primary growth lever for the technology platform.
As a Senior Applied AI/ML Scientist, you will shape the technical vision and system design behind these discovery experiences. You will combine query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to deliver personalized results.
Candidates with a product-focused mindset and a bias toward execution will thrive here. You should enjoy moving quickly from research papers to prototypes and production while collaborating with scientists and engineers.
What you will do
- Build next-generation search ranking algorithms by integrating deep learning and machine learning to personalize the retailer discovery journey.
- Leverage large language models to extract multimodal text and visual signals to better profile user intent.
- Partner closely with teams across the company to experiment and improve machine learning models for search ranking and beyond.
- Design and productionize natural-language search and discovery systems that generate relevant collections and assist retailers.
- Share best practices regarding deep learning model development, agent-workflow evaluation, and MLOps through code reviews.
- Provide technical guidance to help teammates level up their skills.
What you need
- Have at least five years of industry experience building large-scale machine learning models with business impact and shipping solutions to production.
- Accumulate a minimum of three years of focused experience in search, recommendation, or ads ranking.
- Hold a Master's degree or PhD in Computer Science, Statistics, or a related STEM field.
- Demonstrate strong programming skills in Python, Java, or an equivalent language.
- Possess hands-on experience with deep-learning libraries such as PyTorch and big data technologies like Spark.
- Show a deep understanding of machine learning best practices including training, serving, A/B testing, and feature engineering.
Nice to have
- 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
- Industry experience building search and recommendation systems for e-commerce or two-sided marketplaces
- Experience using AI tools like Cursor, Claude Code, or Codex for code development
- Familiarity with Kotlin
Benefits
- Competitive pay
- Equity
- Comprehensive benefits designed to support your life inside and outside of work
Skills and tech stack
Questions candidates ask
What is the remote work policy?
Faire operates on a hybrid schedule where employees go into the office three days per week on Tuesdays, Thursdays, and a third flex day of their choosing. Additionally, hybrid in-office roles have the flexibility to work remotely up to four weeks per year.
What is the salary range for this role?
The pay range for this position in San Francisco is $211,000 to $290,500 per year. The role is also eligible for equity and benefits.
What tools and technologies will I work with?
You will work with deep learning libraries like PyTorch, big data technologies such as Spark, programming languages like Python and Java, and large language models. The team also utilizes enterprise AI tools to support daily productivity.