# AI Research Engineer at LanceDB

> United States · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/ashby%3Alancedb%3Ad72f807c-7d73-4356-8f49-4597293aa5ef (read 2026-11-06).

## Facts (observed)

- Company: [LanceDB](https://alderhq.app/companies/lancedb)
- Location text: United States
- Where it can be done from (inferred): United States (evidence: "Location: United States")
- Posted: 2026-09-14 (52 days ago)
- First seen by alder: 2026-11-03 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/lancedb/d72f807c-7d73-4356-8f49-4597293aa5ef
- Skills listed (inferred): Python, PyTorch, LLMs

## Pay and sponsorship

- Posted pay: $150k–$255k per year (from the listing's pay field)
- Market band for similar posted roles (United States, n 672): p25 $183k, median $223k, p75 $277k

## Description (the employer's text)

### 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

As the AI research engineer at LanceDB, you'll work with the research team to perform fairly open ended research, focused on end to end training flows across different AI domains, showcasing how LanceDB can be used to accelerate research flows.

This is an opportunity to pursue your research interest as an engineer, and have a meaningful impact on raising awareness and significantly improve the product.

### What You'll Do

Show how Lancedb can be used for training models end to end from curation to modeling across industry verticals

Compare the Lancedb stacked workflow with existing standard training flows with well designed and replicable experiments, that may include benchmarking

Provide core content and work cross-function with to increase awareness for workflow specific features like blobv2, distributed indexing etc.

Publish models and research papers on LanceDB blog platform, social media, and in AI conferences

Partner closely with engineering and product to provide feedback from a researcher’s perspective

### What We're Looking For

5+ years of experience in training deep learning models, not limited to LLM, ideally have worked with video, action, world models before

Proven track record of training SOTA models in an industry vertical

Strong experience in building and maintaining popular OSS repos.

Demonstrated ability to map user feedback from noise to key deliverables

Excellent prioritization skills and demonstrate execution efficiency

Strong sense of product GTM, demonstrate ability to balance strategic thinking with hands-on execution

Passion for staying up-to-date with SOTA AI research and trends

### Nice to Have

Experience with training transformer based models, and post-training/alignment

Hands on experience with PyTorch, distributed training, and tensor parallelism

5+ years of experience, including working at startups

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Alancedb%3Ad72f807c-7d73-4356-8f49-4597293aa5ef and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.
