Staff Software Engineer, ML Search

• →Own pipelines and DAGs that move data, features, embeddings, and models through the ML lifecycle
• →Design/maintain ranking and retrieval services that run models in real-time
• →Build scalable model-serving APIs, ensuring reliability, efficiency, and performance
• →Create reusable infrastructure that other MLEs depend on to train, deploy, and iterate on models
• →Ensure pipelines and systems support high scale, low latency, and operational excellence
• →Enable modeling with better systems, features, and deployment pathways

• 8+ years of industry experience with a focus on search and recommendation systems.
• 6+ years of  experience in designing, building and iterating large-scale search relevance and infrastructure systems, handling end-to-end system development.
• Proven track record in delivering large and complex systems with big business impacts. 
• Knowledge and experience working with search systems (e.g. Lucene, Solr, ElasticSearch, Opensearch etc.).
• Demonstrated expertise at cross-functional collaboration - successfully shipped several large-scale projects with complex dependencies across teams.
• Proficient in object-oriented programming (Python, Golang).
• Experience in API design and integration with GraphQL, REST, HTTP, Thrift or gRPC.
• Experience of developing applications using large-scale data stack - e.g. Kubeflow, Airflow, BigQuery, Kafka, Kubernetes, Redis etc.

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.