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Starburst

Enterprise-ready Trino data analytics platform

Applied AI Research Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeUnited States

About the Job

Requirements

  • At least 3 years of experience in information retrieval, natural language processing, knowledge representation, or applied machine learning research.
  • Production experience building retrieval-augmented generation, grounding, or retrieval systems rather than prototypes or demos.
  • Strong evaluation methodology, including benchmark design, statistical analysis, and reproducible experiments.
  • Ability to operate at the research and systems boundary by reading research papers and shipping code.
  • Fluency in Python and experience with vector databases, embedding models, and large language model application programming interfaces.
  • A track record of converting research insights into shipped production systems.

Responsibilities

  • Design and build grounding systems that connect agent reasoning to verified enterprise data sources.
  • Build and optimize retrieval pipelines, including retrieval-augmented generation, hybrid search, and structured query generation, for accuracy and latency.
  • Define data representation strategies that preserve semantic fidelity across heterogeneous enterprise data, including catalogs, schemas, and lineage.
  • Create evaluation frameworks comprising automated benchmarks, regression suites, and human evaluation protocols.
  • Convert validated research findings into production systems that ship to users.
  • Establish quality metrics and dashboards that track agent correctness week over week.
  • Build feedback loops in which user interaction data flows back into evaluation datasets and informs grounding improvements.

Desired Qualifications

  • Experience with enterprise data systems, including SQL engines, data catalogs, and schema metadata.
  • Familiarity with text-to-SQL or structured query generation.
  • Published research or open-source contributions in information retrieval, natural language processing, or evaluation methodology.
  • Experience designing evaluation pipelines that run in continuous integration and continuous delivery.
  • Familiarity with JVM-based systems.

About the Company

Starburst

Enterprise-ready Trino data analytics platform

Starburst provides an enterprise-grade distribution of the Trino SQL engine and professional support to run fast analytics on data lakes and other sources. It offers Starburst Galaxy (cloud) and Starburst Enterprise (on-prem) with extra connectors, security features, and enterprise support. The system connects to popular tools like Tableau, Power BI, Looker, and Python clients, enabling seamless data access across different data sources. Users access and query data through the Trino engine, which coordinates queries across data sources and returns results via familiar BI or programming interfaces. Starburst differentiates itself by adding enterprise-grade security, governance, and connectors on top of Trino, plus both cloud and on-prem options. The company’s goal is to help customers gain faster, more reliable data insights and better decision-making by enabling scalable analytics across data lakes and other sources.

Company size
501-1,000
Company stage
Series D
Total funding
$414M
Headquarters
Boston, MA
Founded
2017

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