AI/ML @ StockX:

Our AI/ML Team is on a mission to build the next-generation e-commerce platform for the next generation customer. We build world-class, innovative experiences and products that give our users access to the world’s most coveted products and unlock economic opportunity by turning reselling into a business for anyone. Our team uses cutting edge technologies that handle massive scale globally. We’re an internet-native, cloud-native company from day 1 - you won’t find legacy technology here. If you’re a curious leader who loves solving problems, wearing multiple hats, and learning new things, join us!

Job Description

In the Search & Recommendation ML team, we work together to productionalize custom machine-learning models that can drive product vision and customer impact at scale. We are looking for a Sr Software Engineer who is sophisticated in large-scale search systems. This member will be responsible for the health of the Search Backend system and working with other ML engineers for productionizing ML innovations in the Search Domains. If you’re passionate about search performance, ranking pipelines, and search index maintenance, this role is for you.

What You’ll Do:

• Design and maintain the infrastructure behind our core search stack.
• Build scalable, fault-tolerant indexing pipelines for real-time and batch data ingestion.
• Partner with ML engineers and relevance teams to support offline/online ranking experimentation.
• Optimize search latency, throughput, and uptime using observability tooling and performance profiling.
• Collaborate with product and data teams to understand query patterns and evolve system design accordingly.
• Drive migration to more modern indexing and vector search frameworks.
• Implement safeguards and autoscaling policies to ensure SLAs under traffic spikes and failovers.

Qualifications

Basic requirements:

• 6+ years of experience building scalable backend systems; ideally in search, recommendation, or large-scale data retrieval.
• Strong experience with search engines
• Solid grasp of distributed systems (e.g., Kafka, Kubernetes, microservices architecture).
• Proficiency in Go and Python.
• Comfort with performance tuning and profiling low-latency systems.
• Experience deploying and operating production systems in cloud environments (AWS, GCP, Azure).
• Familiarity with Databricks, Unity Catalog, or Lakehouse architecture is highly desirable.
• Bachelor’s or Master’s in Computer Science, Engineering, or a related technical field.

Preferred requirements:

• Familiarity with MLOps, vector databases (e.g., Faiss, Milvus, Weaviate), or ANN algorithms.

• Experience with Kubernetes and Docker for productionalizing models.
• Experience in building machine learning systems at scale.
• Experience in using AWS Cloud Platform, Databricks and/or OpenSearch or Elastic Search
• Experience in LLM serving / Open AI or equivalent / Langchain / Agents / RAG Apps