<story><title>Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]</title><url>https://www.youtube.com/watch?v=sEciSlAClL8</url></story><parent_chain><item><author>minimaxir</author><text>Although TensorFlow&amp;#x2F;Keras allows anyone to implement Deep Learning easily, that doesn&amp;#x27;t mean that they will get &lt;i&gt;hired&lt;/i&gt; for a relevant job position without a PhD. Most Deep Learning jobs, and even relatively mundane Data Scientist jobs nowadays, want a PhD from my experience. There is a surplus of Statistics&amp;#x2F;CS PhDs, why would a company hire someone without one if they do not have to?&lt;p&gt;Without a relevant job position, knowing how to implement Deep Learning is a buzzword trick for Medium thought pieces or getting $$ in funding from venture capitalists for a generic &amp;quot;AI&amp;quot; startup that no one actually understands how it works.</text></item></parent_chain><comment><author>agibsonccc</author><text>I have seen this from multiple angles.&lt;p&gt;I used to teach at a data science bootcamp where many of the students got hired by big companies.&lt;p&gt;I&amp;#x27;ve also been running  a deep learning startup for the last few years and have hired quite a few people.&lt;p&gt;Many of our team don&amp;#x27;t have phds but can still write backprop code for even complex modules like inception among other things. A lot of my students didn&amp;#x27;t have phds either.&lt;p&gt;A few of us (me included) are self taught. I&amp;#x27;ve also coauthored the largest oreilly book on deep learning:
&lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;shop.oreilly.com&amp;#x2F;product&amp;#x2F;0636920035343.do&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;shop.oreilly.com&amp;#x2F;product&amp;#x2F;0636920035343.do&lt;/a&gt;&lt;p&gt;1 piece of advice I would offer is building something that differentiates you from the rest. Many of these &amp;quot;medium thought pieces&amp;quot; you&amp;#x27;re talking about are actually very cool applications of deep learning. If you want to get hired for these kinds of roles, I would demonstrate you understand how to build things with deep learning. The litmus test I would also look for is &amp;quot;I trained a net from scratch and innovated in x way&amp;quot;. Honestly, there&amp;#x27;s a rare amount of talent out there that can do well at software engineering as well as deep learning. I&amp;#x27;m not convinced a phd is a hard requirement.&lt;p&gt;I get that recruiters at these larger companies definitely tend to look for the buzz words and often can&amp;#x27;t tell the difference so it&amp;#x27;s definitely harder going the traditional route.&lt;p&gt;Tech hiring also tends to be a networking thing as much as it is buzz word bingo no matter what field you&amp;#x27;re in. If you can network a bit and build something cool that demonstrates an understanding of deep learning I don&amp;#x27;t see the problem.</text></comment>
<story><title>Tensorflow and Deep Learning, Without a PhD, Martin Gorner, Google [video]</title><url>https://www.youtube.com/watch?v=sEciSlAClL8</url></story><parent_chain><item><author>minimaxir</author><text>Although TensorFlow&amp;#x2F;Keras allows anyone to implement Deep Learning easily, that doesn&amp;#x27;t mean that they will get &lt;i&gt;hired&lt;/i&gt; for a relevant job position without a PhD. Most Deep Learning jobs, and even relatively mundane Data Scientist jobs nowadays, want a PhD from my experience. There is a surplus of Statistics&amp;#x2F;CS PhDs, why would a company hire someone without one if they do not have to?&lt;p&gt;Without a relevant job position, knowing how to implement Deep Learning is a buzzword trick for Medium thought pieces or getting $$ in funding from venture capitalists for a generic &amp;quot;AI&amp;quot; startup that no one actually understands how it works.</text></item></parent_chain><comment><author>elliott34</author><text>I think one of the only companies doing this right, and that has the resources to do this right, is facebook, as they seperate AI research and teams that are focused on putting these things into production (i.e. ML engineers vs Ml researchers). Trying to combine these two things into the same role is resulting in continued confusion and frustration. I like this Stitchfix article as an overview (&lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;multithreaded.stitchfix.com&amp;#x2F;blog&amp;#x2F;2016&amp;#x2F;03&amp;#x2F;16&amp;#x2F;engineers-shouldnt-write-etl&amp;#x2F;&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;multithreaded.stitchfix.com&amp;#x2F;blog&amp;#x2F;2016&amp;#x2F;03&amp;#x2F;16&amp;#x2F;engineers...&lt;/a&gt;)</text></comment>