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Datakami | ML Engineer | Netherlands (within 2hrs of Nijmegen) | Remote (NL, DE, BE) | No visa sponsorship | https://datakami.com

We're a software engineering consultancy specialized in generative AI. Small team of senior ML engineers offering remote expertise to startups across US/Europe, solving unique challenges of running generative AI in production.

Looking for ML engineers who are a mix of ML expert, software engineer, researcher, and hacker. You'll work embedded in client projects on: - Converting bleeding-edge open source AI models to production - Building production LLM pipelines from scratch - Improving models on speed, robustness, and performance - Designing custom LLM benchmarks and evaluation - Building and scaling ML infrastructure - Setting up monitoring, tracing, and prompt management

Tech stack: Python, LLMs, AWS/GCP, MLOps tools, Docker, Git, Nix

We value: self-starters, quick learners, strong communication skills, software quality, open source. Role involves engineering, talking to clients and outreach.

Requirements: Strong Python, experience with production LLM systems, cloud platforms, MLOps. Must be EU work eligible and live within 2 hours of Nijmegen, Netherlands. Remote work with occasional meetups.

Benefits: 25 days PTO, home office budget, professional development budget

Apply: https://datakami.com/careers

Recruiters/freelancers/agencies: we're not working with recruiters or considering freelancers or agencies at this time.

To provide some counterweight to all the overwhelmingly positive reviews:

I've used kagi for 6 months and have over 7500 searches with them. It mostly works, but there are a few downsides compared to Google:

- The latency is a lot higher than google, taking over a second to display any results. - The results are often not as relevant, I have to frequently retry my search in Google. - The results for anything local (I'm not in the US) are abysmal. Searching for anything in my city instead only gives me results for the city's history.

Still, I persist in using Kagi, mainly because it's not Google and I want them to succeed. The results are frequently good enough for me to stay with them.

I'm not sure that the answers that the model provides have anything to do with what it's actually doing. The way they seem to be prompting it also exhibits this issue, where they first have it arrive at a conclusion and then come up with an explanation for this conclusion. LLMs do not have an inner voice to reason with, and tokens generated later do not influence earlier tokens (unless you're doing beam search, but you mostly aren't). It would be much improved if asked to do reasoning first and then arrive at a conclusion.

Sourcegraph seems to have collected a bunch of these (now leaked) email addresses from signups on self-hosted instances.

I remember being very surprised when I was signed up to their mailing list after I made an account on my self-hosted instance, and I'm not sure about the ethics (and legality) of collecting these in the first place.

SEEKING WORK | Europe (CET) | REMOTE

We're a 2 person team doing on-demand research, development and prototyping, specializing in generative AI & LLMs.

Our services include: AI Strategy, custom LLMs, prompt engineering, NLP, dataset vetting

Recently used technologies: langchain, llama-index, python, datasette, llama.cpp, stable diffusion, typescript

Website: https://datakami.nl/

Email: hello@datakami.nl

They actually found the bug and released a fimware update fixing it before anyone's SSD was 5000 hours old, and SSD owners (at least back in those days) are generally expected to install firmware updates. It was quite well-publicised, too; they handled it really well, except for the actual release.