Ask HN: Who is hiring? (September 2026)

We treat research, engineering, and creativity as first-class citizens. We're looking for engineers to join our research, product, and GTM teams.

What we value (staff & company writings):

- AGI: https://www.matthewnewton.com/blog/arc-challenge-diffusion

- Diffusion research: https://re-n-y.github.io/devlog/rambling/steering/

- Pragmatic LLM reflections: https://maxemitchell.com/writings/i-read-all-of-cloudflares-...

- Low-level computing: https://gab-menezes.github.io/2025/01/13/using-the-most-unhi...

- Open-sourcing AI research: https://www.krea.ai/blog/flux-krea-open-source-release

Current projects:

- WebGL2/WebGPU for node-based tools & CRDTs for collaboration

- Large-scale multimodal model training

- Cross-service metrics, tracing, and observability

- LLM-driven JS bundle optimization

-- To apply, email austin+hn@krea.ai (use the +hn suffix to make sure your email is prioritized!)

(I want to preface that we don't have a ton of budget to expand our team right now and we want to keep the team small, but I also don't want to miss someone who would be a great fit)

We are a self-funded independent AI research lab in Zurich. Currently we explore ARC-AGI3, LLM/RL reasoning, and quant. We recently started a new LLM post-training and pre-training effort, led by some ex-engineers from the swissAI Apertus team. We also like to do some Kaggle on the side, our team includes the top #3 and #12 globally.

Our overall roadmap is to catch up with LLM capabilities, own the full stack, and use it to do our own independent research, pushing efficiency and looking for new paradigms. We expect our new cluster (2x NVL GB300) to be up by the end of the month.

Long term we want to switch to AI alignment/safety research as I believe this is all that matters when AI capability is high enough.

We look for people who are driven, who believe it's possible to make significant contributions to both AI capabilities and safety, and with previous experience pre-training and post-training LLMs and related infra.

If interested, email me at benjamin at tufalabs ai.

We are a small boutique consultancy and are quite experienced. A lot of us have extensive consultant experience. You will join a small, highly skilled remote team of engineers and transformation practitioners working at the forefront of enterprise AI.

We use AI for both development and in our solutions. We are looking for engineers that are critical thinkers, understand the limitations of AI but also where it can have a positive impact.

Apply at: https://grnh.se/wr97lgu2teu

Our website: https://egg-ai.com/

We're looking for cracked, optimistic engineers/students with good systems taste and high tolerance of ambiguity. We're a team of ~10 in SF, building a GPU neocloud. High agency, lots of freedom, very little boundaries.

Think GPU datacenter bring-up, storage, networking, and designing IaC. Also think optimizing AI workloads, env design, minimizing GPU bring up times, and maximizing hardware fungibility.

Email sasan at inferra.ai with anything relevant. For internships: please tell what you'd like to do in the next ~year, if you could do anything.

I'm hiring for a frontline EM building the automation and trust layer for freight pricing, matching, onboarding, and settlement.Lead 1-3 teams (FTE + contractors), own delivery end-to-end, ~8 yrs exp typical. I expect everyone in my eng org (myself included!) to be technical and be able to help unblock the team, though your day-to-day wont be in the code.

Technical here means you can/will get into the code yourself and architecture reviews and maintain technical credibility with our junior to staff/principal level engineers. These are not player-coach roles, but these are frontline roles that need that technical capability.

Interesting problems: trust/fraud at marketplace scale; legacy-data-meets-modern-stack; and all kinds of problems that come with powering hundreds of thousands of load/shipment postings every day.

AI/LLM: We are leaned in, but still hold humans responsible for what they push and expect everyone to review and understand llm output before asking other humans to look at a thing.

Culture: I am deeply familiar with Google's project oxygen/aristotle and am building a culture where our teams can do great work with minimal bs.

Location: Must be local to one of our three locations (Seattle, Portland, Denver).

Primary Tech: Node/TS, React, GraphQL, Kafka/redpanda, k8s, AWS, etc

https://careers.dat.com/jobs/?gh_jid=6139594004

Reach out directly at .+hn@dat.com; I am the hiring manager for these roles. I'll junk anything that smells of AI.

My profile and background: https://www.linkedin.com/in/kelvin-luu/