If we are going to have a future workforce in the area of engineering and computer science, we must start educating students while they are young. And yes, we must be honest with these students. You will have to enroll in advance math classes and learn how to solve problems. This is one of the setback of recruiting good students to major in the area of engineering. Many of today's students entering college are not prepared for college based on a recent study conducted by Center for Community College Student Engagement, http://www.ccsse.org/center/. We as a community have to do a better job encouraging and preparing students for college. When a child enter first grade, one of the first word they need to learn is COLLEGE.
Besides the reasons covered here, it could be that younger engineers with some experience flock to "sexier" fields than what a particular company offers.
Fresh graduates, especially in need of visa sponsorship, could choose a bigger company regardless of its attractiveness.
Same with older folks like us who may lack hot high-demand skills.
I dont think Google or Facebook (or Apple) have issues with finding right candidates.
This problem is even more pronounced in traditional industries: a friend of mine who works in old school high voltage electical enginnering, complains for years that it is impossible to find good candidates - they are all gone to microelectronics.
My sympathy @Mbt_1#1, there are many peoplelike you...yet, we are reading about this Google engineer who turned down $500,000 offer as Google pays him $3M annually already...interesting world we live in...Kris
Well, I am an emgineer in my early 30's, with 10 years of industry experience, and am having a difficult time finding an job. I fit right in the middle of this category, and am supposedly the missing link. I am currently employed, but looking for something new. Everywhere I go I get "We like what you have to offer, but we are looking for someone with more experience." I'm not sure how I fit into this equation, but I think employers are just being too picky. They see the downturn as an opportunity to be selective, so they set their sights high - too high, and are surprised when they have a hard time finding someone to fit their "perfect candidate". In my opinion, they need to choose candidates that match most of their requirements, and work with the new hire to develop the areas they are lacking. There is no such thing as a purple squirrel!
@Yog-Sothoth:Employers want their folks to work yet more hours to be productive. Yet this was never the plan, we are doing this to compete with far east working practices. Are we just lazy ?
We are all in favor of competition when it benefits us in terms of lower prices and increased choice. We are far less thrilled when we have to compete.
The global economy is increasingly flat. As a rule, work flows to where it can be done cheapest. Union efforts and government regulations at best delay the inevitable. The rise of the Internet means that many technical jobs can actually be done from any location, so there is no requirement to hire someone who lives where the company is located to do the job.
When we buy goods and services, we look for the best deal. Wages are a business expense, funded by the revenues gained through sales to customers. Since price is an area in which companies compete, they have a strong incentive to keep labor costs down to be able to offer attractive deals to customers.
So employers, as a rule, will pay only as much as they have to to get the employees they need, will think hard before they add new employees, and may look at reducing headcount to reduce the wage bill.
To command a high salary, one or both of two things must be true: you must either be a scarce commodity - you are one of the few people who actually knows how to do what the employer wants - or you are in an area with high costs of living, and employers in that area must pay more for local workers to provide a living wage. (Stats I saw a while back had salaries for comparable positions 100% higher in San Jose than in West Virginia, because its cost so much more to live there.) And being a scarce commodity is transitory. Today's hot skill set is tomorrow's latest thing to outsource. You can earn high wages for a time, but cannot expect that state to continue. All too soon, there will be other people who can do what you do and will be willing to do it cheaper.
The challenge for today's worker is to make themselves worth what they'd like to be paid. Value is relative. Something is worth what someone else will pay for it, and employers are looking for the best deals just like everyone else. It doesn't (and shouldn't) mean putting in extreme hours. It may mean figuring out how to accomplish that much work in the time frame you want to work. Call it an engineering challenge.
Are we lazy? Probably not. But we aren't used to having to compete.
I agree completely, something changed radically in the way HR is being handled. Of course back when we still had a healthy defense industry it would have been unheard of to even think about "too much" experience! But now not only has that industry been sharply defunded, there's some new thinking along the lines of "manned aircraft are obsolete in modern warfare" and other ideas that are equally premature to be declared completely resolved that COULD tend to render older technologies somewhat less in demand and similarly those who designed in them. But I think perhaps what's been creeping into the more commercial side of the business could be more of an "Asian" approach to human resources and personnel management that I can't completely quantify. Of course the acceptance of these premises also sounds the death knell for corporate support of ideas like "continuous education" and introduces the concept that it's perfectly OK to throw a decent employee on the scrap heap if there's a cheaper (therefore more "acceptable"?) candidate waiting in the wings. This is all of course HORRENDOUSLY shortsighted and will cripple the industry and poison corporate reputations for decades, but I guess it's not that easy to "stop progress", especially when no one is willing to listen to the premise that it really isn't?
If companies don't take the responsibility to help train young engineering graduates on the job, as they have always done in the past, then these companies have no business complaining that young people are discouraged from enrolling in STEM majors in school. If young grads can't find jobs, what message does that send to kids entering college?
A company looking to hire only engineers in a tight time window of 5 to 10 years experience should figure out that just maybe, other companies are also looking to that narrow window, and consequently they have created their own shortage. "Too young or two old" means that there are many engineers outside a 5-year span of experience? Come now. Doesn't that sound a bit contrived?
While we aging semiconductor engineers are working fewer hours, many of us are still working part time. The key seems to be to adjust your salary expectations for the reality of globalization in manufacturing, and deregulation of the financial gambling systems (a really great paying job as only quant in the "banking" game?) I simply kept lowering my expectatations and going to where the work was offered. And now that can be done from home, via Google Hangouts and high speed data mining.
The math is quite similar, since automation in manufacturing and in finance have taken us to the point where knowledge workers are either experts at structuring information and data, or experts at predictive modeling of that data. And the CEO's are just good looking well dressed folks that need some quants around to assure their bonus each quarter.
What used to be called "machine learning algorithms" such as nearest-neighbor or genetic or neural models can be used on streaming sensor data from machines, or on cash flows and options trading and with some hardware (and knowlege on how to use it) high speed trading is much like high speed manufacturing.
What we really need to bring this late 1980's brain drain to its logical conclusion is to automate the bungie-CEO jobs, by simply letting the quants and the customers work more cooperatively, getting the C-suite out of the way. Just a thought. Financial Engineering and Semiconductor Engineering require similar skills to great extent (with some specialized but very old physics and some specialized but not only old but flawed econometrics being the only serious difference perhaps.
My best teacher at Carnegie Tech in 1950's said that the last job to be automated out of existence would be heavy equipment operators, since automation of hand-eye-coordination was more difficult than the management and engineering decision processes given powerful computers. And I notice that Google is testing out high speed hand-eye coordination, so maybe these overpaid CEO's really have no clothes at all??? Might be an interesting experiment. Many startups did fine until they were told to hire a CEO. Maybe its time to finish automating those non-value-added jobs and keeping the quants productive without so many middle men preventing the customer from being served well? Lean Six Sigma Supply Chain adjusted in real-time by Customer Satisfaction Algorithms?
Wow, I totally agree with the "you are the problem" sentiment! Although I apply it at both ends -- to young and older engineer candidates.
Since when have US companies insisted on hiring just a narrow age group of engineers? With just enough experience to land running full tilt, and young enough that they will potentially stay for decades?
It may be true that we need more young people to enroll in STEM majors at universities, but it's equally true that we need corporate managers responsible for hiring people to quit with the excuses already. Tech companies traditionally have hired young kids straight out of school, and then invested perhaps a couple of years in getting these young people to full operating strength.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.