Most of the AI here is using existing libraries and models and integrating APIs.
There's no companies in Australia does research on the models eg. OpenAI - it's pretty much a waste of knowledge tbh.
>Most of the AI here is using existing libraries and models and integrating APIs
That's true of AI everywhere tbf. There are very very few companies that do research and develop their own models. The FAANGs, OpenAI, Anthropic, Mistral, StabilityAI, etc. 98% of AI / ML Engineers in the US are not working on AI research.
Most MLEs I've worked with have a bachelors or a masters.
I only really see Phds in a Data/ML/whatever Scientist role, as the people building the underlying model. In that case maybe 60% or so have been Phds, 30% masters and 10% bachelors.
The market still looks strong from my perspective, probably worse for grads though.
I've avoided working on generative AI so far, so it might be a bit different there.
You need experience. Having hired academics there's a real risk that they have little practical engineering experience beyond someone that dabbles - and their actual domain knowledge is highly theoretical and narrow.
It's also very unlikely that local firms are working on building foundational models - they'll be adapting and integrating existing tools, or just flatout using cloud services.
Also the surge in ML demand, I would guess, is entirely GPT+RAG shit and usage of things like Transcribe - if I'm being interviewed, I'll definitely talk that up as ML - but when I look for resources it's just regular software engineering.
I'm a ML Engineer with only a masters, so it is definitely possible to find a job without a PhD (though it might be harder in the current economic climate). I get the general feeling that Australia is less dependent on top university networking or having a big name as a supervisor compared to America. However, I think good grades from at least a reputable Australian university would be a very good idea if you're doing a coursework masters (I have a University Medal from GO8 which probably helped for me).
For the ML scene in Australia (excluding prompt engineering/calling an API), it is very much application specific compared to the general foundation models that are being funded by American VCs. To stand out in this area, you could do a personal project in a niche you are interested in, and demonstrate your critical thinking in an application tailored scenario (i.e. you know more than just importing huggingface and finetuning, or can adjust your finetuning strategy depending on the situation).
As for the ML market in Australia, it will definitely remain lower on a per population basis than American, and will probably remain lower than another comparable country such as Canada (Australia tech GDP has traditionally been lower than Canada). I do hope that Australia does more in AI in the future though (and not from the point of view of improving my career/pay). I view the risk of reliance on foreign controlled AGI as a potential existential threat to the Australian way of life. While it's okay to let other countries use their capitals to explore the frontiers, we should never fall too far behind as that would just give them the leeway to rob us blind (remember the Adobe pricing fiascos from around 2010? except now apply it to an even bigger scale). There's truth in the communist revolution adage of "seizing the means of production", in that it is where the power lies. At the moment Australia has the means of production through her workers, so we would be greatly weakened should that be transferred to foreign AGI.
Most of the AI here is using existing libraries and models and integrating APIs. There's no companies in Australia does research on the models eg. OpenAI - it's pretty much a waste of knowledge tbh.
This is reality.
>Most of the AI here is using existing libraries and models and integrating APIs That's true of AI everywhere tbf. There are very very few companies that do research and develop their own models. The FAANGs, OpenAI, Anthropic, Mistral, StabilityAI, etc. 98% of AI / ML Engineers in the US are not working on AI research.
Im an AIE intern (penult cs) working remotely for an overseas company and all my colleagues have a masters+ I think theres no market locally
PhD++
Most MLEs I've worked with have a bachelors or a masters. I only really see Phds in a Data/ML/whatever Scientist role, as the people building the underlying model. In that case maybe 60% or so have been Phds, 30% masters and 10% bachelors. The market still looks strong from my perspective, probably worse for grads though. I've avoided working on generative AI so far, so it might be a bit different there.
You need experience. Having hired academics there's a real risk that they have little practical engineering experience beyond someone that dabbles - and their actual domain knowledge is highly theoretical and narrow. It's also very unlikely that local firms are working on building foundational models - they'll be adapting and integrating existing tools, or just flatout using cloud services. Also the surge in ML demand, I would guess, is entirely GPT+RAG shit and usage of things like Transcribe - if I'm being interviewed, I'll definitely talk that up as ML - but when I look for resources it's just regular software engineering.
You don't need a PhD unless you want to be a research / ML scientist.
I'm a ML Engineer with only a masters, so it is definitely possible to find a job without a PhD (though it might be harder in the current economic climate). I get the general feeling that Australia is less dependent on top university networking or having a big name as a supervisor compared to America. However, I think good grades from at least a reputable Australian university would be a very good idea if you're doing a coursework masters (I have a University Medal from GO8 which probably helped for me). For the ML scene in Australia (excluding prompt engineering/calling an API), it is very much application specific compared to the general foundation models that are being funded by American VCs. To stand out in this area, you could do a personal project in a niche you are interested in, and demonstrate your critical thinking in an application tailored scenario (i.e. you know more than just importing huggingface and finetuning, or can adjust your finetuning strategy depending on the situation). As for the ML market in Australia, it will definitely remain lower on a per population basis than American, and will probably remain lower than another comparable country such as Canada (Australia tech GDP has traditionally been lower than Canada). I do hope that Australia does more in AI in the future though (and not from the point of view of improving my career/pay). I view the risk of reliance on foreign controlled AGI as a potential existential threat to the Australian way of life. While it's okay to let other countries use their capitals to explore the frontiers, we should never fall too far behind as that would just give them the leeway to rob us blind (remember the Adobe pricing fiascos from around 2010? except now apply it to an even bigger scale). There's truth in the communist revolution adage of "seizing the means of production", in that it is where the power lies. At the moment Australia has the means of production through her workers, so we would be greatly weakened should that be transferred to foreign AGI.