Senior Software Engineer
LanceDBAbout the role
About LanceDB
AI advances at the speed of its research, and research moves at the speed of its data. LanceDB is the AI-native Multimodal Lakehouse: one system where a researcher curates petabytes of video, audio, and every signal derived from them with a few lines of Python, and the next training run starts as fast as the next idea. Customers like Runway, Midjourney, and Netflix build the future of AI on LanceDB, from frontier and world models to robots and autonomous vehicles.
About The Role
We're looking for a Senior Software Engineer to help expand the reach of Lance and LanceDB within the broader data infrastructure ecosystem. You'll work at the intersection of high-performance computing, big data, and open-source systems. You will contribute scale and performance improvements, integrations with the wider data and AI ecosystem, simplifying distributed operations, and usability and maintainability enhancements.
What You'll Do
Designing and maintaining efficient distributed Lance dataset operations
Building efficient indices to enable predicate pushdown and accelerate queries in Spark, Ray, or Trino
Working on table formats, data encodings, and various aspects of the Lance format in Rust
Driving open-source community efforts to integrate the Lance format with Spark, Hive Metastore, Presto, Trino, Ray, and other data infrastructure systems
Operating and improving internal data processing infrastructure
Promoting the Lance format in open-source communities and at Big Data conferences
What We're Looking For
10+ years of experience building high-performance databases, big data systems, or large-scale data services
Deep understanding of internals of open-source Big Data or AI training systems (e.g., Hadoop, Spark, Flink, Ray, Iceberg, Delta Lake, Hudi, ClickHouse, Trino, Presto, PyTorch, or JAX)
Strong experience with high-performance computing in C++, Java, and/or Scala
Experience with Rust (or willingness to learn it)
Proven ability to move fast, work independently, and collaborate with a high-caliber team
Nice to Have
Contributor, committer, or PMC member in Apache or other large open-source projects
Experience with Apache Arrow, DataFusion, Parquet, Iceberg, or Delta Lake
Track record of driving large features or integrations in distributed systems
Strong community presence and passion for open-source collaboration
Responsibilities
- Designing and maintaining efficient distributed Lance dataset operations
- Building efficient indices to enable predicate pushdown and accelerate queries in Spark, Ray, or Trino
- Working on table formats, data encodings, and various aspects of the Lance format in Rust
- Driving open-source community efforts to integrate the Lance format with Spark, Hive Metastore, Presto, Trino, Ray, and other data infrastructure systems
- Operating and improving internal data processing infrastructure
- Promoting the Lance format in open-source communities and at Big Data conferences
Qualifications
- 10+ years of experience building high-performance databases, big data systems, or large-scale data services
- Deep understanding of internals of open-source Big Data or AI training systems
- Strong experience with high-performance computing in C++, Java, and/or Scala
- Experience with Rust (or willingness to learn it)
- Proven ability to move fast, work independently, and collaborate with a high-caliber team
Skills mentioned
About LanceDB
LanceDB is the multimodal lakehouse for AI: the unified foundation for AI data, where every type lives together in open format in your own cloud. It unlocks AI curation, feature engineering, and training at scale on datasets too large and too mixed for a stitched-together stack to handle. Frontier labs and generative-media teams run their training, search, and curation on LanceDB, including Netflix, Runway, Midjourney, and World Labs.