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Show HN: Prompt Engineering Jobs
- KomoD 4y agoIs this a serious website? "Prompt Engineer 20 years of experience"
- tough 4y agoApril fool's late submission?
- tough 4y agoSeems real tho, redirects to actual jobs. Guessing its a scraper, maybe some of the jobs are fake like the one asking 20y experience lol. I want to be a Cannabis Prompt Engineer now https://www.xing.com/jobs/muenchen-remote-cannabis-ki-prompt-engineer-ms-contact-project-99313621 https://www.xing.com/jobs/muenchen-remote-cannabis-ki-prompt...
- Oras 4y agoIt is scraping jobs at the moment, you are right. I'm afraid these kind of job postings asking for experience longer than technology will always be there. I have removed the post now.
- UncleEntity 4y agoNow it’s “ Prompt Engineer 20 ans d'expérience”. They seem pretty determined to find that one candidate.
- tough 4y agoA time traveler from the future
- swader999 4y agoFeels for the people that made a living by googling for stuff. They are going to have to upgrade.
- devmunchies 4y agoMany think prompt engineering is just like being good at writing Google searches, where my job is to be good at knowing "how Google/GPT4 thinks"—good at writing a single query. However, I think prompt engineering will evolve to be an actual technical role, akin to Data Engineering (the people who make the systems, pipelines, ETL jobs, etc for the data). Prompt engineers will build systems that facilitate prompt generation. Meaning that prompts will be dynamically generated or at least partially generated with modifications or additions to the raw user prompt. It's the difference to being able to write HTML vs being able to do all the backend work to dynamically generate the HTML for my Amazon homepage (including the performance benchmarks and other strategic requirements), for example.
- maxbondabe 4y agoI'm working on a prompt engineering product at a stealth mode startup. Would it be possible for me to pick your brain sometime? I'd like to understand more about your workflow, and how our product could fit into that. No pressure. My email is in my profile.
- sgrove 4y agoI’ve been doing the same thing with a number of projects, building chains of prompts from one api call to another e.g. for ConjureUI (self-creating, iterable UIs that come into existence, get used, then disappear) https://youtu.be/xgi1YX6HQBw https://youtu.be/xgi1YX6HQBw how it works to generate a full self-contained react component: 1. Take user task 2. Pass it to a prompt that requests a Product UI description of a component 3. Pass 1+2 to another that asks for which npm packages to use 4. Pass 1+2+3 to a templated prompt to write the code in a constrained manner 5. Run 4 in a sandbox to see if there are errors, if so pass it back to #4, looping It’s currently quite slow, but that’s an implementation detail I think.
- dorilama 4y ago> 3. Pass 1+2 to another that asks for which npm packages to use I see a fresh new generation of supply chain attack, or more prompt engineering to hopefully filter out malicious packages
- monero-xmr 4y ago“Poke this box different ways until the right stuff leaks out”
- sokoloff 4y ago"Jiggle this bag of parts until the device assembles itself."
- simonw 4y agoClassic XKCD: https://xkcd.com/1838/ https://xkcd.com/1838/
- capableweb 4y agoEssentially what many software "engineers" do day-to-day.
- TobyTheDog123 4y agoI disagree. I believe that a critical part of software engineering is the ability to trace and resolve an issue through many different systems and code paths (what most people call debugging) There is no way to debug these models, there is no way to systematically fix your prompts. It is therefore completely guesswork on what words in what orders might produce results closer to what your stakeholders expect. Software engineers, when presented with an issue, can dive down as deep as they want (hell, even to the machine code layer if it comes down to it) in order to fine-tune, fix bugs, or do whatever else a stakeholder might expect. Two very different coins in two very different universes.
- capableweb 4y ago> There is no way to debug these models, there is no way to systematically fix your prompts. It is therefore completely guesswork on what words in what orders might produce results closer to what your stakeholders expect. I think if you spend some more time with these models, or any similar model where you have X input > Y output, you notice that you can in fact "debug" those as well, without knowing 100% of the internals. Some fixes are better than others. There are better and more reliable ways to steer these models, compared to other ways. It is not 100% guesswork, some people are better at it than others.
- WolfOliver 4y agoThe goal should be to be able to just talk your model without any engineering. If you as a normal user can not interact with an AI then the AI is just not smart.
- simonw 4y ago"AI" isn't smart. Doesn't mean it's not useful if you know how to use it.
- roundandround 4y agoI hope Andrew Ng was correct that a great many methods end up largely equivalent given the same amount of input because the current methods deliver a rather useless result. With a google search you are getting citations and stuck finding the truly good ones that truly match, with chatgpt you are getting an answer from someone who read all those citations and treats them all as equally good. I think the real problem was to get the most perfect citations given your specific question. We can forgive the error since it took the web a few years to discover that best is rarely a fresh bit of blog spam by a moron who has read everything and refuses to cite sources. So GPT is convincingly as good as a human blogger yet not as useful as a less human emulating tool.
- capableweb 4y agoThe goal is for the end-user to just be able to talk to your model. But to get there, there is some additional "engineer" needed to be done. What does "smart" mean to you in this context?
- simonw 4y agoHere's my rebuttal to the inevitable flood of "prompt engineering is dumb / a bug not a feature" comments: https://simonwillison.net/2023/Feb/21/in-defense-of-prompt-engineering/ https://simonwillison.net/2023/Feb/21/in-defense-of-prompt-e...
- darkteflon 4y agoReally enjoying your writing on LLMs. Thanks Simon.
- scottiebarnes 4y agoAll the job listings seem to be actual software/ML engineering roles and not really "prompt engineering" roles.
- submeta 4y agoWhen it comes to making ChatGPT solve technical problems, my observation is that you need to be good at writing (technical) requirements to be good at writing prompts. When I assign a task to a (human) developer, the results depend on two things: First, how good the developer is, second, and more importantly, how well and clearly I am expressing the requirements. And this is also true for ChatGPT. With very precise requirements I get very good results. So prompt engineering is like writing good requirements, and that also requires understanding the problem domain.
- ChatPGT 4y agowriting/reading/understanding good requirements is a really nice skill to have in this decade. I have a peer that just CAN NOT interpret what is going on so he always need to schedule a meeting and it pisses me off hard. "are you able to talk right now?" sigh
- amrocha 4y ago"Prompt engineering" isn't real. What are you engineering? You're throwing shit at the wall and hoping it sticks. Software Engineering is kinda fake, especially in industry, but at least that's an actual discipline. "AI monkey" is a better description
- williadc 4y ago> You're throwing shit at the wall and hoping it sticks. A more charitable description might be "You're employing the scientific method to extract value from GPT-like systems." Just like in science, with time you're developing intuition for how the underlying system works, but you still have to run the experiments.
- amrocha 4y agoOk, then it's not "prompt engineer", it's "researcher" or "analyst".
- haxton 4y agoWould you prefer "LLM Reverse Engineer" then?
- iguana 4y agoThis is an unhelpfully cynical take. The job title has "engineer" in it, so a more charitable interpretation is more serious than "AI monkey". Using LLMs to solve real problems is not easy. Making sure that you don't introduce regressions while making improvements is difficult, and requires building and evaluating a dataset, and the necessary pipelines. It may also include diversification of LLM providers, and creating the necessary abstractions. A fundamental understanding of how LLMs work, ability to compare different architectural approaches, along with typical data engineering and software development skills would be required. What if you want to use the LLM for Question/Answer systems that requires working with embeddings? What if you want to find a way to process data locally without sending sensitive data to the LLM provider? This requires real engineering skills.
- romland 4y agoI'm convinced this will be a common job description for a few years, after which it will flow into and just become a part of any other job. Like Googling. I mean, we all know it does take some domain knowledge to be able to use it in your job. Also just like Googling. We've started calling it LLMing (llemming). Edit: Specifying prompts is leaning towards specification. I am not saying googling is that. I'm saying that, like googling, it will just be a part of the job in a not distant future.
- G_z9 4y agoPrompt engineering. Just stick engineering at the end of your job description and all your self consciousness about how useless you are will go away.
- 000ooo000 4y agoAs a HN Comment Engineer, I take great offense to this. I have passed this on to my team's Retort Engineer. Stand by.
- G_z9 4y agoComment engineer. It’s a job that’s already been made redundant by prompt engineers. A prompt engineer can spin up hundreds of comments in seconds that would have taken dozens of comment engineering man hours. We should also be worried about legal engineers and legislation engineers.
- bee_rider 4y agoRetort Engineering is mostly involved in the design stage, they can send a prototype, but you probably would be better off contacting the Technicians in “Snarky one-liners.”
- seydor 4y agoUpvote engineer here to provide my Certified upvote
- game_the0ry 4y agoNice. Given the wild popularity of posts about prompt engineering "jobs" paying +$300k, it was only a matter of time for an indie hacker to create a job board specifically for this type of job.
- angarg12 4y agoI've also read the articles about prompt engineers with no experience or technical skills commanding six figures, or the one about these jobs paying +300k. I have a BSc and Master's in Computer Science, 14 years of experience, I have slowly climbed the ladder, got a FAANG job 5 years ago, and only last year I managed to break 300k salary for the first time (working in ML of all things). Am I losing my sanity or these reports are greatly exaggerated?
- deleted 4y ago[deleted]
- lupire 4y ago> articles about prompt engineers with no experience or technical skills commanding six figure Please share an example. I've only seen articles claiming this might exist, based one attention-seeking job ad from one company, which didn't claim "no experience or technical skills".
- csomar 4y agoWelcome to the bubble.
- game_the0ry 4y agoNo, you are not losing your sanity, those reports are greatly exaggerated.
- Oras 4y agoOP here, I see lots of comments about prompt engineering thinking in the context of asking one question to get the answer. In that perspective, I understand why many people think it is useless. However, if you tried to make a chain of functions/calls, or worked with a tool like LangChain [0] you will see its importance. Ex: "Which stock had better performance in the last 6 months, Tesla or Microsoft?" A question like this would check: - Understanding this is a financial question. - Get the stock ticker (symbol) for each one. - Use an API to get their performance history in the last 6 months. - Compare. - Return the answer. [0] https://github.com/hwchase17/langchain https://github.com/hwchase17/langchain
- throwaway1851 4y agoAnd, with that, we’re back to pre-LLM chatbot design: intent classification, entity extraction, business logic, return a result. Only the whole process rests on a more rickety foundation. It’s also bloated and slow, querying an LLM over and over for these things. I’m starting to see some parallels to modern JavaScript and SPAs. ;-)
- photonbeam 4y agoMore like technician
- xkcd-sucks 4y agoMy prediction that we'll have psychologists for computers before having a mechanistic understanding of cognition seems to be coming true :)
- meghan_rain 4y agolmao at the job saying "20 years of experience in prompt engineering required"
- blibble 4y ago"boilerplate generator"
- TobyTheDog123 4y agoI have one of these jobs currently. It is a nightmare for me, and I do somewhat regret taking the contract even with the sizable hourly rate. In my eyes, programming makes sense. Even if I introduce bugs, I can sooner or later track down the issue, facepalm, resolve it, and move on with my day, with some semblance of accomplishment and lessons learned. My prompt engineering work offers no such rewards, and is a total time-suck. This is because, as another commenter wrote here, it is "throwing shit at the wall and hoping it sticks." While you can treat it as a scientific endeavor, testing hypotheses against a black box, you will never find a prompt that works consistently, even with a low temperature, solely because these models were not built to give consistent results. There is no end-all solution, there is no "correct prompt." Companies employing prompt engineers are looking for such consistency. Prompt engineers are therefore stuck in a system where they simply cannot succeed. They can hope and pray that the testing done by managers produces fruitful results upon every test, but the results are, for all intents and purposes, random.
- ukuina 4y agoThank you for the honest peek behind the curtains. Are the companies enamored with the productivity gains of prompt-based systems sufficiently that they can ease up on the requirement for consistency?
- TobyTheDog123 4y agoIn most cases prompt engineers are hired solely to achieve consistency, in order to reliably integrate the responses into other areas of their stacks which may only be able to handle certain kinds of inputs. Let me give a real example (cant go into too much depth but this is generic enough). I was told to create a prompt that would make ChatGPT generate ten of the hottest real estate markets: "You must always format this data in exactly the following format: ${index (as a single numeral)}: ${name of location} ${median housing price} ${YoY increase} ${link to internal system} ${number of available locations}" You would think this would be a pretty easy task for ChatGPT/Davinci to handle, but like I said, consistency is completely missing. - Sometimes it will say "Market ${index}" instead of just the number, even with the single numeral qualifier. - Sometimes it will comma separate the data, even if there are explicit instructions not to do so - Sometimes it will provide the prices/percentages/numbers as regular integers, sometimes it will format them, again, even if explicit instructions are provided - Sometimes it will place an empty space in between the lines, even if there are explicit instructions not to do so - Sometimes it will place random punctuation at the end, even if there are explicit instructions not to do so It's entirely random, you could have a 4000 token prompt or a 40 token prompt, and the results will be of the same quality. Usually, this is fine for content generation. But content formatting? Anything remotely specific? Forget about it. All of the models (I haven't been able to try ChatGPT 4 yet, however) will simply ignore things, even if (and I promise it's the last time I'll say this) there are explicit instructions not to do so.
- ukuina 4y agoThis would be a great resource for GPT to find humans who can prompt GPT better.
- zerop 4y agoWill knowing deep learning help on writing better prompts for LLMs?
- hbarka 4y agoThis exchange: “I have a strong suspicion that “prompt engineering” is not going to be a big deal in the long-term & prompt engineer is not the job of the future. AI gets easier. You can already see in Midjourney how basic prompts went from complex in v3 to easy in v4. Same with ChatGPT to Bing. To the extent that prompt engineering remains a thing, it might be the Era of the Humanities Major.“ https://twitter.com/emollick/status/1627804798224580608 https://twitter.com/emollick/status/1627804798224580608
- rrmdp 4y agoNice one! I think Prompt Engineering Jobs could become popular
- atum47 4y ago> Prompt Engineer 20 ans d'expérience I don't speak french but it clearly says 20 years of experience. Talk about trolling.
- asasidh 4y agoPrompts are kind of like SQL in the structured database world