5 months ago
Base Salary
$160k - $210k/yr
Responsibilities
- Develop solutions for information retrieval, ranking, semantic search, query understanding, and recommendation systems.
- Build and optimize low-latency, high-throughput search APIs, indexing pipelines, and retrieval systems.
- Evaluate search technology and drive decisions involving indexing strategies, retrieval architecture, and performance tradeoffs.
- Lead work from research design and experimentation through productionization and customer-facing delivery.
- Design evaluation frameworks for relevance, precision and recall, ranking quality, and user engagement signals.
- Improve query understanding using embedding models, vector search, hybrid retrieval, and query rewriting.
- Investigate anomalies in search performance, ranking behavior, and data freshness and trace issues to root cause.
- Partner with Product, Engineering, and client stakeholders to improve search experience and discoverability.
- Mentor teammates and improve experimentation rigor, system design, and operational excellence.
Requirements
- 5+ years of experience across machine learning, software engineering, data science, or data-intensive product systems.
- Strong Python programming proficiency and experience operating in cloud environments, preferably AWS.
- Production-level expertise in at least two of information retrieval, ranking systems, NLP or embedding models, and distributed systems.
- Experience designing, fine-tuning, and operating high-scale backend systems, APIs, or data delivery platforms.
- An advanced degree in a quantitative discipline or equivalent deep industry experience.
- Strong judgment with noisy or implicit relevance signals and ground truth.
- Ability to communicate technical concepts and tradeoffs to technical and non-technical audiences.
- Collaborative, ownership-oriented approach suited to fast iteration cycles.
- Preferred experience with Typesense, Python, AWS, Elasticsearch, OpenSearch, or FAISS.
- Preferred experience building customer-facing search or recommendation systems, APIs, query understanding, embeddings, LLM-powered retrieval, or hybrid search systems.
- Preferred experience mentoring senior engineers or data scientists.
Benefits
- Equity is included as part of the compensation package.
- The employer provides additional benefits and opportunities as part of total compensation.