The open-source database for AI applications
LanceDB, headquartered in San Francisco, California, is an open-source database designed specifically for AI applications. It provides hyper-scalable vector search capabilities and advanced retrieval for retrieval-augmented generation (RAG), making it ideal for developers working with large-scale AI...
Employees at LanceDB enjoy competitive salaries, equity options, flexible remote work policies, and generous PTO to promote work-life balance....
LanceDB fosters a culture of innovation and collaboration, prioritizing developer experience and open-source contributions. The team values transparen...
LanceDB is a developer-friendly, open-source data lake for multimodal AI. From hyper-scalable vector search to advanced retrieval for RAG, from streaming training data to interactive exploration of large-scale AI datasets, LanceDB is the best foundation for your AI application, and powers some of the most groundbreaking applications and challenging requirements today.
We are seeking an engineer who brings both hands-on model training, model fine-tuning, feature engineering expertise and a strong background in data/AI/ML infrastructure to join our world-class team, pushing the frontiers of multimodal data infrastructure.
Resident expert on AI engineering, bringing familiarity with frameworks such as PyTorch or JAX.
Champion a superior Developer Experience, maximizing productivity for AI engineers.
Drive the end-to-end design and development of a high-performance and large-scale feature engineering infrastructure for leading multimodal AI companies.
Collaborate closely with the customers, design partners, and the Lance/LanceDB community
You like working with a small, high-caliber team with a lot of autonomy and drive, and you can iterate fast.
You have 3+ years of experience building and deploying ML/DL models in production environments or supporting infrastructure for AI researchers and AI engineers performing these tasks, using Python and libraries such as PyTorch or Tensorflow.
You have a proven ability to deliver projects end-to-end, from scoping and resourcing to implementation and delivery.
You have a working knowledge of cloud platforms (AWS, GCP, Azure) including managed storage (S3, GCS) and compute (EC2, GKE, AKS).
You have knowledge of monitoring/logging stacks (Prometheus, Grafana, ELK/EFK) for alerting on data pipeline failures, resource saturation, or model skew.
Has a deep understanding of training architecture, from PyTorch or Jax experience to CUDA kernel fusion or TPU programming.
Has experience designing or operating a feature store (e.g., Feast, Tecton) or building a custom feature registry.
Has understanding Docker layered file system, K8s, Slurm, scheduling algorithms, and orchestration services.
Loves python wizardry or Rust
Has experience directly working with external customers
Has built sophisticated monitoring and observability features
Has hands on knowledge of Kubernetes, Terraform, Docker, CI/CD. Or experience operating Kubernetes services in production environments.
Is familiar with one of Apache Spark, Apache Flink, Delta Lake, Ray, Google Dataflow, Kafka, Airflow, Kubeflow or other similar systems.
You’ll join a world-class team of open-source builders (co-authors of pandas, and contributors to HDFS, Arrow, Iceberg, and HBase) working on cutting-edge AI infrastructure. You’ll collaborate on systems that power next-generation AI workloads while shaping how LanceDB operates and scales production environments.
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