Senior Backend Engineer - Ads ML System

About this Role:

Faire’s Ads teams are building the next generation of marketplace intelligence — powering personalized discovery and efficient ad delivery for our brands and retailers. Our systems connect the right products with the right buyers through intelligent pricing, auction mechanisms, and large-scale retrieval and ranking pipelines.

As a Senior Backend Engineer, you’ll take ownership of the core algorithms and infrastructure that shape the way our ads and search systems decide what to show, to whom, and at what price. You’ll partner with Data Science and Infrastructure teams to design training workflows, deploy models, and operate low-latency inference services, owning the end-to-end model lifecycle (feature generation → training → evaluation → deployment → monitoring) for Ads retrieval, ranking, and pricing.

This role offers a rare opportunity to shape both product and technical direction in a fast-moving, high-impact area at Faire.

What You’ll Do:

• Own critical services within our Kotlin-based backend, driving reliability, scalability, and low-latency performance across billions of ad and search events.
• Design and evolve large-scale retrieval, ranking, and pricing systems to optimize relevance, performance, and marketplace efficiency.
• Develop auction-based delivery systems and scoring pipelines that balance advertiser ROI with retailer experience.
• Collaborate cross-functionally with Data Science to prototype, evaluate, and productionize machine learning models and their training workflows.
• Build and operate online inference services (e.g., feature access, real-time scoring, canary/shadow deploys) with clear latency and reliability SLOs.
• Mentor engineers and contribute to team best practices in design reviews, performance tuning, and system architecture.

We’re Excited About You Because You Have:

• Experience: 5+ years in backend systems, including 2+ years in designing, deploying, and scaling ML inference and online serving systems.
• Technical Depth: Proficiency in Kotlin, Java, or similar object-oriented languages; comfort with distributed systems, service design, and performance optimization.
• ML Fluency: Hands-on experience with model training pipelines and operating production online inference/serving, including deploying models to real-time scoring paths on ads/search/ranking.
• Collaboration: Strong communication skills and a track record of partnering with cross-functional stakeholders, from DS to PM, to deliver complex systems.
• Mindset: Curiosity and a drive to understand complex market dynamics; passion for applying data and algorithms to real-world business problems.
• Education: Bachelor’s degree in Computer Science/Engineering or equivalent industry experience.

Technologi