Ah, what a wonderful role. I'm sad I've missed the application period, maybe one of the only jobs in tech I'm specifically qualified for :(.
I should add the asterisk that my anecdotes on the presumed legitimacy of publishing solely iNaturalist data comes from conversations I've had in the American endangered/threatened plant conservation community. More common or non-American species occurrence data from iNaturalist likely has more legitimacy being used directly in publications.
In the US we have a series of government/NGO controlled databases that house sensitive species data, so often our scientific community has to operate through them to get access to publishable information (of which the raw data is then often obscured, just used for analytics). In my experience iNaturalist data is often a good starting place for determining which government bodies/NGOs a biologist should start reaching out for requesting data access.
I love GBIF and have a priority this year of making sure that my organization plugs-in what we're willing to share via IPT or Biocase!
I work in a large conservation organization focused on rare plant conservation.
iNaturalist is sometimes used by our ecologists/biologists as a starting point for collating occurrence data.
The iNaturalist data itself is likely specifically being pulled from gbif. Then they go private/specialty databases that have more spatially and taxonomically accurate records.
But iNaturalist data is often not considered high quality enough to be publishable by itself (wide brush statement) in my field of plant conservation.
We've tried to have some conversations with iNaturalist and they weren't really interest in talking, gave me pause on what their motives as an organization are.
But conservation tools are few and far between, and iNaturalist is a really powerful tool for initial data exploration.
Three things I've noticed as a dev whose field involves a lot of niche software development.
1. LLMs seem to benefit 'hacker-type' programmers from my experience. People who tend to approach coding problems in a very "kick the TV from different angles and see if it works" strategy.
2. There seems to be two overgeneralized types of devs in the market right now: Devs who make niche software and devs who make web apps, data pipelines, and other standard industry tools. LLMs are much better at helping with the established tool development at the moment.
3. LLMs are absolute savants at making clean-ish looking surface level tech demos in ~5 minutes, they are masters of selling "themselves" to executives. Moving a demo to a production stack? Eh, results may vary to say the least.
I use LLMs extensively when they make sense for me.
One fascinating thing for me is how different everyone's experience with LLMs is. Obviously there's a lot of noise out there. With AI haters and AI tech bros kind of muddying the waters with extremist takes.
Lol same, writing SQL and directly wrangling Async connection pools always seemed way easier for me than trying to jam sqlalchemy into whatever hole I'm working with.
It really depends what your industry is. I've been writing some printer drivers for custom hardware + windows applications at work. Much of the technical jargon I've been learning during development involve things like "driver interfaces" and "communication interfaces".
Depending on how recently I'd been working on our printer drivers I also would likely need clarification. Now if the job is "frontend developer" I agree, someone needing to clarify if you're talking about a user interface or communication layer interface is probably a bad sign.
But if it's a looser role I'd definitely look to clarify the question!