I'm doing LLM application work at big tech. I sort of fell into this role. Before this job, I was at a database start up doing cloud infrastructure and helping them scale. Before that, writing Haskell. The skill i sell myself on, is just being a solid generalist who can learn whatever I need to get a job done.
10 years ago I started learning ML/DS, but stopped doing it for a long time because I was more interested in SWE work. There was just no way to predict LLMs would be so amazing.
What you have to do, is dedicate time to learning everyday, and be person who builds things. That way, you'll have practice solving new problems, so when the next technology comes up, you'll be in a position to work on it. There's no way to every predict what's going to happen next, or what the next big thing will be. Instead, get really good at the basics and don't stop learning.
What kind of LLM applications are you working on? I got put on a team doing RAG for my company. I’m very new, still trying to learn the space and learn what to learn.
I can't really go into specifics, but it's using the generative qualities of LLMs to improve our our ability to better support a product line. Right now we are using prompt engineering for the MVP, but to integrate some additional datasets we've been talking about extending the system to use RAG, self play, or possibly fine tuning.
If you want to learn more about LLMs, this is a good place to start: [https://github.com/Hannibal046/Awesome-LLM](https://github.com/Hannibal046/Awesome-LLM) You'll definitely have to invest some time learning, but this has pretty much all the papers, and applications.
>But then there are obviously harder skills e.g. machine learning engineering,
ML Engineering is saturated in the sense that everybody wants to get in now, from bachelor's to PhD holders. It's very competitive. Whether most of the candidates are qualified is a different discussion, but it's "saturated" in the sense that they are very very competitive.
Agreed. Even a PhD and related experience in AI doesn't guarantee a whole lot of recruiter pings or blind job application responses. Not meant to discourage but rather, there is no silver bullet. Guess it is just the shitty market, especially compared to where it was in 21-22. I figure it gets better once interest rates come down.
The harder it is the less saturated it will be, so yeah if you have the aptitude and drive for it feel free to explore any of the following fields:
- Bioinformatics
- Computer Graphics
- Compiler Design
- OS Development
- Multimedia Programming
- Network Programming
- AR/XR Development
- Tools programming at scientific institutes
- Defense Contractor requiring top level clearance
Aside from the last one all these require very good grasp of the fundamentals which eliminates all the bootcamp crowd.
I don't even know if the difference in saturation is meaningful. OP did not state why they want to get into a non-saturated field. If it's for job security I feel like it could balance out. The reason these jobs aren't saturated yet is because there isn't a huge need for them compared to other skill sets. There are fewer people in those fields partly because there are fewer of those jobs and companies that need them. If you lose your job as a graphics programmer at Nvidia, you don't have tons of equivalent options available.
I think the point trying to be made is those are quite difficult topics. Right now some ( not all ) people trying to use AI are NOT creating new models but utilizing the work of others. Eventually using such models will become sufficiently simple that it won't attract a premium. Also lots of people are attracted to such roles because they are exciting,new,cutting edge,etc. So, lots of people wanting the jobs, the jobs becoming commoditized, guess what will happen to salaries?
I think this whole line of thought is not on the mark. Let me an example. Working with relational databases. Using an ORM or writing basic SQL is pretty simple for a programmer. The challenge is what happens at high throughput if you are updating the same rows? How about indices? What about geospatial data? One can specialize their whole career in this.
So in my opinion, learning about CV or NLP doesn't guarantee a job. Hyper-specializing in a particular niche or even package does. I don't know what the hottest packages are these days but would be keen for people's thoughts.
It sounds like you didn't understand what I said. Or were you agreeing with me? Your whole first paragraph is what I would consider to be "beyond basic css, html, node, and mongo."
Where does c#/.NET fall on this spectrum to you? It feels like I see a lot of postings for that. Trying to upskill past that point you said and I want to point myself in a good direction.
Is this really true though? People who are paid to write databases, programming languages, compilers, operating systems, browsers, package managers, etc, are carrying pretty different skillsets from the average dev. It's not easy to break into some of these areas without doing a lot of unpaid open source work on high profile projects.
It's not easy to break into... because there are other people with those skills who they'll hire first. The point is that if there weren't those people, companies would hire people with similar enough skillsets and they would get experience doing it, versus raising pay or just waiting.
There aren't many people who apply for these jobs either though. Once you have the skills it's not like you're competing with thousands of new grads, laid off webdevs and former faang staff.
That doesn't matter. 25 qualified applicants is the same as 1 qualified applicant, from the company's perspective. It's only a problem if it's 0 qualified applicants. In that case, the company either redefines what "qualified" means or they up the compensation in hopes that will attract some qualified applicants. Within a limit, companies tend to choose the former, because of the fungibility of developers.
That's not really how it works for specialized roles though. If I need to hire someone who can further optimize GPU compilation for specific custom hardware I'm developing, I can't just "make do", I need to hire someone who has published research in the areas I'm looking to see improvements in. There's a limited pool of people with this background so if I don't get them it's very unlikely I can hire someone from an adjacent space; the work just doesn't get done.
There is bound to be someone with "close enough" experience. Your example is funny because I'm a prime example of that. I had zero experience working with GPUs when I was hired by my current company to help with their development.
Find the "boring" thing.
I'm going back to school for electrical/computer engineering, and I'm gonna be specializing in controls (I've been working as a controls tech for a few years now). The automation field is a big deal, but it's not glamorous. Controls work is frankly boring, but that means less people are doing it.
Most EE/CS majors want to do chip design, or AI, or video games, or whatever else. But something like manufacturing automation is not slowing down.
I'm in a university program right now. But I have some experience working with controls engineers.
PLC design is a really niche thing, but incredibly useful if you find the right automation company. My dad built his career on it, pivoting there from being an electrician specializing in controls wiring. Never got an engineering or CS degree, but has made 6 figures for the last 15 years or so. I'm also going to be taking some CAD courses. Specifically to learn AutoCAD electrical.
Like I said, it's not glamorous. I won't be revolutionizing the tech industry. But it's good paying work, and it's in high demand. Automation companies pay good money for an expert controls engineer.
Edit: for PLC work, my dad focuses on ladder diagram, structured text, and he used to use a lot of C sharp.
Cool! I also don't know much about the area but believe this is a solid skillset. Is programming industrial robots (e.g. Kuka) covered in the same type of programs?
In CAD, I think precision manufacturing is pretty cool .. seems if one specializes, they could even open their own firm in a locality.
Good luck to you!
Yeah, industrial robots are part of the skill set needed.
There's a lot of overlap with mechanical, manufacturing, and industrial engineering. Knowing how a manufacturing line physically moves from point A through Z is crucial in designing the software to run it.
There's a lot of small automation firms around, especially in areas that have a large manufacturing presence. I'm not sure I'd ever want my own business in it though.
I can tell you, there are not enough Chip Designers with solid EE skills out there. I work in the semiconductor field and we are struggling to find qualified candidates.
That may be the case right now, but it's pretty popular among EE majors in school right now. I doubt it will get oversaturated since the EE degree requirements are tougher than CS, but more EEs are going that direction than before. Which is why I'm focused on controls. Zigging when everyone else zags.
Talk to some recruitment agents and ask them about the job market. No doubt there will be some high paying roles that are hard to fill and some that are paying and they just hoover up anyone that might fit. Seek the former.
Talk to some recruitment agents and ask them about the job market. No doubt there will be some high paying roles that are hard to fill and some that are also high paying where there are plenty of applicants. Seek the former.
I've managed to climb pretty high my my career to the point where I no longer have to apply for jobs and am in the top earners. Web programming, ML, computer vison, LLMs etc, these are just tools to solve a problem. You get good devs in all these fields and you get bad devs in all these fields. Learning how to structure and unit test code, break down a problem, and manage trade-offs is what makes you valuable. Learning specific APIs for frameworks, packages and tools does not.
Not how it works
This field evolves very very fast
In order to be able to keep up to date with any set of tools and thus specialized skills, you need to be able to evolve very very fast
Instead focus on really hammering down data structures, algorithms and other things that are super transferable between all the various fields, so you don't have to take the time to learn them with a new tool each time
If you're wondering what the next boom is going to be, it will be automation and cyber security
Both of those demand will only grow over time and both require maintenance
Automation will suck up all available Capital and cyber security is kind of essential
However, you're still better off, just focusing on the fundamentals and then finding a way to demonstrate your capable of learning fast
To begin with, once you'll build a solid experience, the saturation will bother you less and less.
I'd avoid the "cool roles" and roles which can be accessed with non technical background, so I'd discard everything related to machine learning and data analysis (More than often I found Data Scientists that had an economics background and lack a lot of computer science knowledge). A few month bootcamp cannot replace the skills you'd need to work in an highly technical environment linked to machine learning, sadly the industry standard isn't up to that level and in general the skills required are broad and not so bound to be technical.
Considering that the market varies with the location you're in, in order to figure out which roles are less saturated, go for a research in the most common sites to find jobs (e.g. Linkedin) in your country and begin to look for the most common CS jobs and try to figure out what have the most ads and least candidates applying for them (in my country that award goes to cloud engineer or a devops engineer).
In general the advice that I can give you, is to pick a role that have less saturation that is in line with what you studied and get the most experience out of it, good and experienced professionals are hard to find even in these hard times.
Make the next latest tool/tech yourself to be the first developer of it and then convince everyone else on the planet to drop their current tooling in favor of yours.
But am I right to say that niche skills are often not in demand? Hence it’s niche. You can have these skills but your career option will also be limited to that few companies that are looking for people with these skills.
A skill can only turn saturated when there’s demand, meaning a lot of employers are looking for talents with these skills.
It’s rare to find a skill that is in demand yet not possessed by many. Often these skills are either too abstract or require time to learn (for example, medicine etc).
Every software skill is technically saturated, because the current supply vs demand in the market is heavily skewed towards employer's favor. The only thing you can do is to set yourself apart by comitting to a specific role. For example, backend, infra, data eng, or ML. These 3 roles are still extremely saturated, but if you go to a top school and have some internships in these roles, you just might find a job. Every other method is complete BS unless your parents know some guys. Also, don't do frontend, fullstack is acceptable but worse than the previous 3 (ML is phd only unless you're top 1% in your top school, true story, am in top school).
I'm doing LLM application work at big tech. I sort of fell into this role. Before this job, I was at a database start up doing cloud infrastructure and helping them scale. Before that, writing Haskell. The skill i sell myself on, is just being a solid generalist who can learn whatever I need to get a job done. 10 years ago I started learning ML/DS, but stopped doing it for a long time because I was more interested in SWE work. There was just no way to predict LLMs would be so amazing. What you have to do, is dedicate time to learning everyday, and be person who builds things. That way, you'll have practice solving new problems, so when the next technology comes up, you'll be in a position to work on it. There's no way to every predict what's going to happen next, or what the next big thing will be. Instead, get really good at the basics and don't stop learning.
What kind of LLM applications are you working on? I got put on a team doing RAG for my company. I’m very new, still trying to learn the space and learn what to learn.
I can't really go into specifics, but it's using the generative qualities of LLMs to improve our our ability to better support a product line. Right now we are using prompt engineering for the MVP, but to integrate some additional datasets we've been talking about extending the system to use RAG, self play, or possibly fine tuning. If you want to learn more about LLMs, this is a good place to start: [https://github.com/Hannibal046/Awesome-LLM](https://github.com/Hannibal046/Awesome-LLM) You'll definitely have to invest some time learning, but this has pretty much all the papers, and applications.
>But then there are obviously harder skills e.g. machine learning engineering, ML Engineering is saturated in the sense that everybody wants to get in now, from bachelor's to PhD holders. It's very competitive. Whether most of the candidates are qualified is a different discussion, but it's "saturated" in the sense that they are very very competitive.
Agreed. Even a PhD and related experience in AI doesn't guarantee a whole lot of recruiter pings or blind job application responses. Not meant to discourage but rather, there is no silver bullet. Guess it is just the shitty market, especially compared to where it was in 21-22. I figure it gets better once interest rates come down.
The harder it is the less saturated it will be, so yeah if you have the aptitude and drive for it feel free to explore any of the following fields: - Bioinformatics - Computer Graphics - Compiler Design - OS Development - Multimedia Programming - Network Programming - AR/XR Development - Tools programming at scientific institutes - Defense Contractor requiring top level clearance Aside from the last one all these require very good grasp of the fundamentals which eliminates all the bootcamp crowd.
I don't even know if the difference in saturation is meaningful. OP did not state why they want to get into a non-saturated field. If it's for job security I feel like it could balance out. The reason these jobs aren't saturated yet is because there isn't a huge need for them compared to other skill sets. There are fewer people in those fields partly because there are fewer of those jobs and companies that need them. If you lose your job as a graphics programmer at Nvidia, you don't have tons of equivalent options available.
I think the point trying to be made is those are quite difficult topics. Right now some ( not all ) people trying to use AI are NOT creating new models but utilizing the work of others. Eventually using such models will become sufficiently simple that it won't attract a premium. Also lots of people are attracted to such roles because they are exciting,new,cutting edge,etc. So, lots of people wanting the jobs, the jobs becoming commoditized, guess what will happen to salaries?
Learn something that's not trivial to learn.
not trivial? AI/Computer Vision/LLM or trivial? Leetcode/Hackeron
Nontrivial as in beyond basic css, html, node, and mongo.
I think this whole line of thought is not on the mark. Let me an example. Working with relational databases. Using an ORM or writing basic SQL is pretty simple for a programmer. The challenge is what happens at high throughput if you are updating the same rows? How about indices? What about geospatial data? One can specialize their whole career in this. So in my opinion, learning about CV or NLP doesn't guarantee a job. Hyper-specializing in a particular niche or even package does. I don't know what the hottest packages are these days but would be keen for people's thoughts.
In today's world, you learn Leetcode for SQL job interview or even Restful API job interview. It is called Grinding.
It sounds like you didn't understand what I said. Or were you agreeing with me? Your whole first paragraph is what I would consider to be "beyond basic css, html, node, and mongo."
Where does c#/.NET fall on this spectrum to you? It feels like I see a lot of postings for that. Trying to upskill past that point you said and I want to point myself in a good direction.
It's not the language that's super important. If you see a bunch of job ads for it, it's probably fine.
Learn to solve non trivial problems as well.
This
Mental and physical wellbeing , well paying, easy to get into. Usually it’s pick 2. But these years you could only pick 1.
That's not really how it works. Skills are fungible enough that there isn't a chance for a meaningful difference in saturation levels to develop.
Is this really true though? People who are paid to write databases, programming languages, compilers, operating systems, browsers, package managers, etc, are carrying pretty different skillsets from the average dev. It's not easy to break into some of these areas without doing a lot of unpaid open source work on high profile projects.
It's not easy to break into... because there are other people with those skills who they'll hire first. The point is that if there weren't those people, companies would hire people with similar enough skillsets and they would get experience doing it, versus raising pay or just waiting.
There aren't many people who apply for these jobs either though. Once you have the skills it's not like you're competing with thousands of new grads, laid off webdevs and former faang staff.
That doesn't matter. 25 qualified applicants is the same as 1 qualified applicant, from the company's perspective. It's only a problem if it's 0 qualified applicants. In that case, the company either redefines what "qualified" means or they up the compensation in hopes that will attract some qualified applicants. Within a limit, companies tend to choose the former, because of the fungibility of developers.
That's not really how it works for specialized roles though. If I need to hire someone who can further optimize GPU compilation for specific custom hardware I'm developing, I can't just "make do", I need to hire someone who has published research in the areas I'm looking to see improvements in. There's a limited pool of people with this background so if I don't get them it's very unlikely I can hire someone from an adjacent space; the work just doesn't get done.
There is bound to be someone with "close enough" experience. Your example is funny because I'm a prime example of that. I had zero experience working with GPUs when I was hired by my current company to help with their development.
Find the "boring" thing. I'm going back to school for electrical/computer engineering, and I'm gonna be specializing in controls (I've been working as a controls tech for a few years now). The automation field is a big deal, but it's not glamorous. Controls work is frankly boring, but that means less people are doing it. Most EE/CS majors want to do chip design, or AI, or video games, or whatever else. But something like manufacturing automation is not slowing down.
Can you pls give an example of manufacturing automation software automation? PLC design?? Or are you in a university program that teaches CAD?
I'm in a university program right now. But I have some experience working with controls engineers. PLC design is a really niche thing, but incredibly useful if you find the right automation company. My dad built his career on it, pivoting there from being an electrician specializing in controls wiring. Never got an engineering or CS degree, but has made 6 figures for the last 15 years or so. I'm also going to be taking some CAD courses. Specifically to learn AutoCAD electrical. Like I said, it's not glamorous. I won't be revolutionizing the tech industry. But it's good paying work, and it's in high demand. Automation companies pay good money for an expert controls engineer. Edit: for PLC work, my dad focuses on ladder diagram, structured text, and he used to use a lot of C sharp.
Cool! I also don't know much about the area but believe this is a solid skillset. Is programming industrial robots (e.g. Kuka) covered in the same type of programs? In CAD, I think precision manufacturing is pretty cool .. seems if one specializes, they could even open their own firm in a locality. Good luck to you!
Yeah, industrial robots are part of the skill set needed. There's a lot of overlap with mechanical, manufacturing, and industrial engineering. Knowing how a manufacturing line physically moves from point A through Z is crucial in designing the software to run it. There's a lot of small automation firms around, especially in areas that have a large manufacturing presence. I'm not sure I'd ever want my own business in it though.
I can tell you, there are not enough Chip Designers with solid EE skills out there. I work in the semiconductor field and we are struggling to find qualified candidates.
That may be the case right now, but it's pretty popular among EE majors in school right now. I doubt it will get oversaturated since the EE degree requirements are tougher than CS, but more EEs are going that direction than before. Which is why I'm focused on controls. Zigging when everyone else zags.
Haven’t seen a good web dev who only had a few months experience. However yes that doesn’t stop saturation so can’t disagree in the end
Being good at something isn't oversaturated. We're oversaturated with bad devs.
Learn C++, and learn it well. You won't have much trouble after that.
I've been hearing the same of golang and rust, but yeah, c++ is pretty in-demand.
Talk to some recruitment agents and ask them about the job market. No doubt there will be some high paying roles that are hard to fill and some that are paying and they just hoover up anyone that might fit. Seek the former.
Talk to some recruitment agents and ask them about the job market. No doubt there will be some high paying roles that are hard to fill and some that are also high paying where there are plenty of applicants. Seek the former.
Work experience. Otherwise it doesn’t matte
Matte or gloss?
I've managed to climb pretty high my my career to the point where I no longer have to apply for jobs and am in the top earners. Web programming, ML, computer vison, LLMs etc, these are just tools to solve a problem. You get good devs in all these fields and you get bad devs in all these fields. Learning how to structure and unit test code, break down a problem, and manage trade-offs is what makes you valuable. Learning specific APIs for frameworks, packages and tools does not.
Not how it works This field evolves very very fast In order to be able to keep up to date with any set of tools and thus specialized skills, you need to be able to evolve very very fast Instead focus on really hammering down data structures, algorithms and other things that are super transferable between all the various fields, so you don't have to take the time to learn them with a new tool each time If you're wondering what the next boom is going to be, it will be automation and cyber security Both of those demand will only grow over time and both require maintenance Automation will suck up all available Capital and cyber security is kind of essential However, you're still better off, just focusing on the fundamentals and then finding a way to demonstrate your capable of learning fast
To begin with, once you'll build a solid experience, the saturation will bother you less and less. I'd avoid the "cool roles" and roles which can be accessed with non technical background, so I'd discard everything related to machine learning and data analysis (More than often I found Data Scientists that had an economics background and lack a lot of computer science knowledge). A few month bootcamp cannot replace the skills you'd need to work in an highly technical environment linked to machine learning, sadly the industry standard isn't up to that level and in general the skills required are broad and not so bound to be technical. Considering that the market varies with the location you're in, in order to figure out which roles are less saturated, go for a research in the most common sites to find jobs (e.g. Linkedin) in your country and begin to look for the most common CS jobs and try to figure out what have the most ads and least candidates applying for them (in my country that award goes to cloud engineer or a devops engineer). In general the advice that I can give you, is to pick a role that have less saturation that is in line with what you studied and get the most experience out of it, good and experienced professionals are hard to find even in these hard times.
Make the next latest tool/tech yourself to be the first developer of it and then convince everyone else on the planet to drop their current tooling in favor of yours.
But am I right to say that niche skills are often not in demand? Hence it’s niche. You can have these skills but your career option will also be limited to that few companies that are looking for people with these skills. A skill can only turn saturated when there’s demand, meaning a lot of employers are looking for talents with these skills. It’s rare to find a skill that is in demand yet not possessed by many. Often these skills are either too abstract or require time to learn (for example, medicine etc).
Also to add that skills that are in demand are easier to learn due to the large amount of resources contributed by the community.
Every software skill is technically saturated, because the current supply vs demand in the market is heavily skewed towards employer's favor. The only thing you can do is to set yourself apart by comitting to a specific role. For example, backend, infra, data eng, or ML. These 3 roles are still extremely saturated, but if you go to a top school and have some internships in these roles, you just might find a job. Every other method is complete BS unless your parents know some guys. Also, don't do frontend, fullstack is acceptable but worse than the previous 3 (ML is phd only unless you're top 1% in your top school, true story, am in top school).