AI Researcher — AI Architecture Research
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 283d ago
The date the source published, not the day we noticed it (2026-01-23). Last seen at its source 5h ago.
We have tracked this listing since 7 Aug 2026 (87 days). The employer's own board has carried it every time we have read it since 19 Aug, when our records begin, most recently 5 hours ago.
Is it remote?
Remote (world)
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
Available worldwide
The description states no restriction of its own. This is the source's own tag.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Ashby employer's own board first seen 87d ago · last seen 5h ago
The listing
About the Role
We’re looking for an AI Researcher focused on AI architecture research to help design, analyze, and advance next-generation model architectures. You’ll work at the intersection of theory and production—publishing novel research while collaborating closely with engineers to turn ideas into real systems.
This role is ideal for someone who has published research papers and wants to see their work directly shape deployed models, not just benchmarks.
What You’ll Work On
Research and design novel AI architectures (e.g. alternatives to standard Transformer designs, long-context models, efficient sequence modeling, hybrid architectures)
Explore architectural improvements for scalability, efficiency, and stability
Prototype and evaluate new architectures through ablations, benchmarks, and empirical studies
Author and co-author research papers for top ML conferences and journals
Collaborate with engineering teams to translate research into training and inference systems
Stay current with state-of-the-art research and identify promising directions early
What We’re Looking For
Strong background in machine learning research, with a focus on model architecture
Publication record in ML/AI venues (e.g. NeurIPS, ICML, ICLR, COLM, ACL, EMNLP, arXiv)
Deep understanding of:
Neural network architectures
Sequence models and attention mechanisms
Training dynamics and optimization
Hands-on experience with PyTorch or JAX
Ability to reason rigorously, design clean experiments, and communicate results clearly
Comfortable working in a fast-moving startup environment
Nice to Have
Experience with non-Transformer architectures (e.g. RNN-based, state-space, hybrid models)
Work on long-context or memory-efficient models
Open-source research contributions
Experience bridging research and production systems
Background in efficient training or inference-aware architecture design
Why Join Us
High ownership over research direction and roadmap
Clear path to publishing impactful work
Tight feedback loop between research and real-world deployment
Small, highly technical team with strong research culture
Competitive compensation and meaningful equity