Information Retrieval Jobs

The Voyage AI team at MongoDB is building state-of-the-art embedding models and rerankers for accurate and efficient unstructured data search and retrieval, crucial for RAG, recommendation systems, and semantic search. This team, comprised of AI researchers from top universities, was recently acquired by MongoDB and is integrating its advanced embedding models with MongoDB's data platform to create powerful end-to-end solutions. We are seeking a Staff Research Scientist to contribute to the development of next-generation AI models, tackling complex challenges at the intersection of machine learning research and the practical deployment of large neural networks.

$151k - $297k

Databricks

Databricks is seeking a Senior Staff Applied AI Engineer to lead the development of context retrieval systems for Databricks agents across various SaaS providers. This is a foundational role focused on building both the underlying retrieval stack and the intelligent search subagents that leverage it. The goal is to significantly enhance the ability of Databricks agents to access and understand relevant information from diverse data sources, thereby improving their performance in tasks ranging from answering complex queries to debugging and data analysis. This role requires deep expertise in information retrieval and a proven track record of shipping production-ready retrieval systems for RAG and agentic workloads.

$229k - $343k

As a Search Engineer at You.com, you will blend deep analytical thinking with practical engineering skills to investigate, develop, and implement novel solutions for our search indexing systems. Your work will focus on advancing the core technology that powers our search engine, ensuring that our index is comprehensive, up-to-date, and optimized for speed and relevance. You will collaborate closely with cross-functional teams to translate complex research into practical, scalable applications. This is a remote position open to candidates based in the United States.

$190k - $260k

Greptile is seeking a Research Engineer to join their AI code reviewer team. This role involves experimenting with and applying the latest advances in agents and language models to enhance product performance and capabilities. You will design and build multi-agent systems, harnesses, models, and evaluations that power code validation. The position offers the opportunity to study multi-agent architectures, prototype and evaluate workflows, and integrate successful prototypes into production systems, while staying current with research in LLMs, information retrieval, and developer tooling.

$180k - $280k

Parallel Wireless is seeking a Senior Applied AI Evaluation Engineer to enhance how their RAN R&D organization analyzes engineering tickets. This role will focus on improving Root-Cause Analysis, recommending ownership, and learning from resolved cases by building rigorous evaluation datasets, establishing baselines, and comparing internal and external tools. The primary goal is measurable, evidence-based improvement, assessing the accuracy, grounding, calibration, and usefulness of AI-generated conclusions for engineering teams. A secondary focus involves analyzing engineering workflows to identify bottlenecks and opportunities for process improvement.

Parallel is seeking a Member of Technical Staff focused on Retrieval & Indexing to build and operate the systems powering our large-scale full-text index over the web. This role involves the entire lifecycle, from deciding corpus content and building searchable structures to developing signals and models for source quality and freshness, and efficiently serving queries. You will proactively identify and address architectural bottlenecks to ensure our systems scale with increasing demand.

$150k - $300k

Parallel is seeking a researcher who thinks like an engineer, or an engineer who thinks like a researcher, to join our team. You will design and train the models that power Parallel's APIs, focusing on the intelligence layer that helps AI agents find exactly what they need from the open web. This role involves tackling research problems at hyperscale, such as training embedding models that capture semantic intent, balancing model expressiveness with sub-second retrieval latency, and maintaining index freshness. You will be building information retrieval systems reimagined for the LLM era, combining classical IR techniques with modern deep learning at a scale that demands new solutions.

$150k - $300k