 to this session of the Linguistics Career Launch. My name is Alex Johnston, and I will be hosting and introducing our presenter today. And our session today is called Human-Computer Interaction Jobs and Industry Overview. And our presenter today is Kelsey Krause. And I will let her give a fuller introduction to herself as she begins her presentation today. Thank you so much for being here, Kelsey. Thanks, Alex. Let me pull up my, I have a little slide deck I wanna share with you all while we go through this. Thumbs up if you can see my screen maybe. Great, okay. Thanks so much for attending this. I'm gonna talk today a little bit about human language technology and industry, just kind of a brief jobs overview. I want to kind of say upfront that while I do work at Cisco, I am not representing Cisco in any official capacity today. I'm just here as a linguist in tech and I wanna share my experience that I've had going through this process with you all. So let's get going. So I'm gonna do a brief intro of myself first and then we're gonna jump into two kind of distinct sections. So first, what careers are like for linguists in tech and then kind of what the process is to apply for these jobs. And I do realize that this is kind of, these are kind of disjoint things. So if you do have questions while we're going, put them in the chat. If I see them, I'll hopefully try to respond to them while we're going, but we can also take those at the end too. So with that said, let's get going. First of all, I wanna just introduce myself. So I was a transfer student to UC Santa Cruz. I did my bachelors in linguistics and in German studies. Once I graduated, I also was a Fulbright English teaching assistant in Germany in Berlin, where I taught English in a high school there. And I finished my PhD in linguistics on kind of the pragmatic interpretation of discourse particles and prosody at UC Santa Cruz in 2018. So that means I've been about three and a half years in the industry and I've also had a couple of pretty distinct jobs. So first of all, I was a consultant. I was a contractor at a Deco, but I was working at Google. There I was working as a linguistic project manager on the speech team. So basically we were creating new text to speech voices for the Google assistant. So in particular, I created or helped create the Hindi English code-switching Google assistant voice as well as a couple of voices in French and in German. After that, so that was a contract position. So after that, I moved on to a full-time position at Amazon where I was a language engineer. And so I'm not sure how much introduction we've had to like language technology stuff before, but language engineers, it's kind of the opposite side of the speech track. So whereas at Google, I was working on the production of the voice from the assistant. On this side, I was working on the interpretation of that voice. So there I was helping to design and build test grammars to train new features for Alexa, specifically for Alexa Auto. So they were building a competitor to Google Maps. So if you have an Alexa and you say something like, Alexa, what's the shortest distance between Santa Cruz and San Jose? That's a feature that I helped implement for better or for worse. So if there are any bugs, I'm not working there anymore, please don't send them to me. And so currently I am working at Cisco. So I am part of voice user interface designer and I also do some data science and data analysis. So I've now kind of worked in all realms as the voice user interface part is, once you have the assistant, which can understand you and talk back to you, you also have to be able to create dialogues and conversations that are going to be natural. So whenever you have a conversation with Siri or Alexa or Google, there's an actual flow behind it that you enter into some sort of dialogue state and we're trying to make natural dialogues there. So there you kind of work a bit more with designers and researchers to refine these voice interactions. And then on the more data science and analysis part of things, we're also looking at the natural language understanding quality. So we do look at feedback from users. We look and see, you know, in log data that we have, maybe a user had an interaction where it ended every single time with them saying no or cancel to the assistant. So then you can go back and look and see, you know, oh, maybe something was happening there that was against the user's expectations. And, you know, you can go back and kind of go through and figure out how you can change those things. So that's a little bit of an intro to me. We're going to now move into careers for linguists and tech. And I see here in the chat that they're going to have a panel on consulting and contracting a little bit. So this is good. This will be a little bit of an intro to to what's to come in there. So I have this big disclaimer here because there is a difference between a full-time employee jobs and tech vendor contractor positions as well. Some of the biggest differences between these things are full-time employees are, you know, the direct and permanent employees of a company. You're usually, you know, you have access to employer-sponsored benefits, so health care equity bonuses, promotions, things like that. You're usually salaried with paid time off and there is relative job security. On the other hand, there is this divide between temps and vendors and contractors where a lot of the times you are working for an intermediary company or a staffing agency, but you're actually working with those direct full-time employees at the company. You're not usually performing the exact same tasks, though. These are usually fixed contracts three to six months. For contractors, those can be extended up to two years. There's some differences between vendors. Vendors can actually be... Their timeframe for working is a little bit longer and this is hourly, generally no PTO, but the contractor-tent vendor category does offer a bit more flexibility in terms of working a lot of the times from where you can work and things like that, although, of course, everything is shifting and changing in the last year. Okay, so I have kind of built this explanation or overview of these types of industry jobs into two continuous. So these are my organization of these things. So don't go looking on Google or whatever to try to find these, these are mine. You can have my slides later, but this is something that I have done to kind of help myself think about what is it that I'm actually looking for in a job? So this first continuum is technically oriented jobs and what I mean by that is what your employer needs or thinks they need in terms of specific quantitative or computational skills. And it's just a pretty basic, I've done it from less technical to fairly technical and we'll go through each of these here. So these less technical positions are things that, they're all things that we have as linguists, right? We have critical thinking skills, there's an emphasis on maybe technical writing or qualitative research. And these tend to be jobs that are a lot more, maybe user focused or customer focused or there's a specific end person that you're going to be working for and maybe working with. So curriculum designers, this company in particular does curriculum for K through 12 schools. There are things like a linguistic project manager at a deco, so that's what I was doing when I was working at Google. So it was a bit less technical in the sense that I didn't need any scripting skills and there was a lot of interacting between people and also projects. So these are gonna be more people on project-based jobs a lot of the times. Moving on to this moderately technical, kind of in the middle portion, those are things where you're gonna have a little bit more of that linguistic data analysis skill where that's gonna be more emphasized. You might need to know a little bit of coding and definitely pattern recognition, which is something that we all have in common, something that we're all pretty good at. That's gonna be something too that really puts you in a good position for these moderately technical jobs. Some job titles you might look for if you think that a moderately technical position is something that suits you well is something like an analytical linguist at Google, language engineer at Amazon or an associate or junior linguist at a deco or memo technologies. And then going on to the fairly technical aspect here, these focus a lot more on skills that maybe we might think are a bit more computer sciencey or computational linguistics adjacent or actually computational linguistics. So things like machine learning, natural language processing, you might need to do a lot of writing and reviewing code and there's like a lot of quantitative research that's really expected of that. I wanna point out too that when you're searching for things you really do need to look at who the job is or like it's not just about the job title, it's about what's in the job description as well because as you'll notice Google, for example, their interpretation of what an analytical linguist does is much different from what an analytical linguist does at Spotify. And the same for the job title language engineer at Amazon versus at a deco. All of these things are out there and available but unfortunately there's not a clear definition of what any of these things mean. I also wanted to point out too that these jobs that I have put in blue, these are all contractor positions. So there's also not a clear distinction between whether or not a job is a contractor position and whether it's a full-time employee position based on the title alone. So what that means for us is that we really do have to focus on job descriptions and what it actually says in the details. But we'll get there in a second. Let me just check the chat. So Aubrey, you ask are most of these positions generally for PhD holders or have you seen people with master's degrees as well in these positions? It really just depends on the company and what they're looking for. I've seen a lot of master's degrees positions. Actually probably most often people get jobs with master's degrees, especially at Amazon and maybe like Spotify. If the fairly technical jobs actually tend to hire a lot of master's students, especially if you've specialized in computational linguistics or some sort of natural language processing machine learning. Ah, yes. And then there will be a session about that. Thanks Emily. So let's move on to the second continuum. So here this is more language oriented jobs. So here maybe you'll want some more linguistic or language expertise or the employer will want a bit more linguistic or language expertise for these particular positions. So that here the continuum is from not language focused to very language focused and you'll notice too that there is some overlap on these two continuum. It's not that these are completely separate. These are just ways, different ways of slicing up the pie. So for these not language focused jobs, these tend to track a bit more with those fairly technical jobs. So there are things like doing data analysis, Python scripting, model failure. A lot of the times they'll have titles like research scientist. Usually these jobs, well, not usually. There are a lot of these jobs that have a position of kind of being like a researcher, like just a regular researcher, but at a big company. Those can be pretty good positions for people with our skill set. So some of the more moderately language focused positions are actually the ones that usually have linguist or language or something in the title that we would recognize as being something that really fits our skill set. So here, you might need some subfield expertise or syntax, semantics, phenology, maybe some project management, maybe some language data analysis. So for example, moderately language focused could be something like you're analyzing failures for why the text to speech voice that you've just synthesized isn't sounding natural. And what you're doing is you're doing linguistic pattern recognition. You are, and maybe you notice that retroflexed consonants aren't being produced with aspiration or not if we're doing the Hindi English code switching voice. And that's something that maybe if you didn't have that linguistics background, you wouldn't be able to hone in on that small piece of data but with that language expertise or with that subfield expertise being able to look at the phenologies and pull out these things, you are able to kind of understand what the problem is and where to go from there. And then the last circle here is the very language-focused things which again, kind of track with the less technical jobs but it's not a complete overlap. So here there's a lot of the technical and creative writing stuff is emphasized but then there's also like actual language analytic expertise. So maybe you're a speaker of Bengali and you need a particular company is looking for people who speak Bengali so that they can go in and annotate utterances. That's where that language expertise would be helpful. Cool. So with that, let's move on to kind of like the question that we've been kind of encountering that for the past couple of minutes which is like, how do you actually look for these jobs? The most obvious thing of course is to go to the actual company that you are interested in and do these keyword searches on those company websites. So keyword search, you think, okay, linguist language but there are all of these less obvious but still relevant things that linguists are working in. Maybe speech data analyst is something that this company thinks linguists do and that's the term that they've decided on. At Apple, for example, there are a lot of linguists that are called ontologists or taxonomists instead of analytical linguists or computational linguists. So there is a lot of searching that you have to do but once you kind of know what to search these are things that they'll come, the jobs will come. And don't worry about writing all of these down. I will send these slides to whoever. Once then maybe I can send them to Emily and she can make them available. So don't worry about that at the moment. Another thing is to look for smaller companies or nonprofits, startups and then also create a LinkedIn profile and set your job search preferences and create job alerts. And it's really, as much as I kind of didn't wanna create a LinkedIn account when I was first looking for jobs, it really, really helps especially the more specific you get in terms of your, in terms of your skills, your skill sets that you have and the things that you say that you are an expert in, that you're interested in, that really helps kind of tailor those job alerts to you and to your skill set. And then again, I won't go through these in any depth because there are a lot of representatives from these linguist career websites at this whole month long event, but these linguist career websites have really great resources for that as well. I'm gonna pause and look at the chat for a second if I think there was something here. Ah, okay, great, good. Okay, so now I wanna move on to a little bit in the last couple of minutes that I have before we open it up to questions about what the job application process really looks like because for me, this was the scariest part, the part with the most unknowns, right? So the one thing that I wanna say is that there's no perfect formula for landing a job whatsoever, but what you wanna do is focus on the things that are actually in your control. So that's what I'm gonna be talking about in the next couple of minutes is like, job prep is about increasing your chances of being hired. And that is about focusing on the things that you can show to others. Oh, thanks, Karina. That you can show to others that you've done. So getting your first job does take some work and also a bit of luck what it will happen. So first of all, here is this hiring process overview. So the first thing you're gonna do is you're gonna submit your resume. Maybe they require a cup for a letter and this is really the part of the process that you control, you own this part of the process. I'm not gonna go super in-depth because I know there's a bunch of other seminars on resumes and all of these things, but this is the process that you're, the part that you control. Then there's also the hiring manager, which is the person that's gonna receive your resume at some point. They usually make the final decision about your hire with the help of the rest of the team who you might interview with. They're gonna be the most knowledgeable about the role day to day. But in between the hiring manager and the rest of the team are the recruiters and this is the wild card here because unfortunately they are usually the least knowledgeable about the role, but they are also the gatekeeper to the role. So it's the recruiter that you need to basically tailor, well, you need to tailor your resume for the hiring manager and the rest of the team, but in a way that the recruiter can understand and that they can then know to pass it along. So the next part of this is all going to be about how you can kind of optimize your chances there. So I've kind of summarized it in three keys to a job search success. So first is define yourself clearly. Second is invest in some tech skills. And then the third is network, even if it feels bad, which I think is what Alex was talking about in that last section that I kind of, that I jumped in on the last couple minutes of. So first define yourself clearly. You want to craft a resume and a profile. I'm going to just kind of talk through this a little bit, not super in depth. Mostly what I want to say is the things to emphasize. So skills, you want to break these into parts which is a really important piece of advice that I got early on. So break it into things like your technical skills, skills that you have in the kind of projects that you've done, and then maybe your language skills. Secondly, it's kind of counterintuitive because we're used to writing CVs where you really emphasize, I worked with this person at this university and we did these projects. You really actually want to de-emphasize your education stuff. A lot of the resumes that I've seen, they'll have like two lines where they got their BA, where they got their PhD or where they got their MA, maybe three, two to three lines and that's it. There's really no other information about that which for someone coming from academia, you think, well, why wouldn't you want to know? And then any supplemental skills or trainings or certificates, projects you've done, use the rest of that space that you might have put, you know, emphasizing the education portion, use that to highlight your skills. So research skills, project management, data collection, all of these things that we do as linguists that we might not think of as project management or data collection or things like that, you want to highlight those things. And then very quickly, I want to talk about tailing your resume to a job posting. So in a lot of the resumes that I've looked at in the past couple of years, there's a little profile blurb at the top. You know, it says something like, where are you graduated from? What your expertise is in? What you're looking for? This piece of advice does mean that you might need multiple copies of your resume. You have to tailor your resume for the job posting, for the recruiter who's looking at the language of the job posting and looking for, you know, for those skills that are in the job posting. So I'm not gonna, you know, read through this again. You can look at this later, but just notice that like the language of this, and I pulled this from an actual job posting. If the language of the job posting says that they are looking for people who know how to improve acoustic and phenology models, maybe you put speech and acoustic patterns in your resume profile. You put things like experimental design, which can, you know, match up with things like train and build models. So, you know, really looking at how the job has been put together what they want in a candidate can really help you have the most success with getting to that recruiter, which means getting to the next level for interviews. Another thing you wanna do is situate yourself as who you are. So, I got a, this may not work for everyone, but I got a piece of advice recently that said, since a lot of our job, the job postings aren't looking for specifically a linguist, what you wanna do is position yourself as a researcher, as a data scientist, first and foremost, as something familiar, and then bring in those linguistic skills on top as something that sets you apart from other candidates in the job pool. So why are you the one to hire? Why are you the one that should get this position? I think thinking about it in this way is easier for recruiters and easier for hiring managers because linguists are kind of few and far between in a lot of companies. And so, you know, just saying that you are this thing but you're also a linguist on top of it might make you stand out that much more. Second key is invest in tech skills. Again, I'm not gonna go through these all one by one because I think there are a couple of sessions on that. But, you know, if you don't have some basic data manipulation skills or know a little bit about speech and language processing, or if you're interested, do some coding courses or boot camps, there's some good free ones out there too. Definitely invest in things like that. And then also kind of as a corollary, know that the skills that you do have already are transferable and know how you can frame it. I'm gonna, again, skip through this a little bit quickly because I wanna make sure that there's room for questions. But the third key is this network, even if it feels bad. So I again, won't go in too much detail because I know Alex has covered a lot of this, but again, if you get this slideshow, these are links to two LinkedIn profiles. I've gotten the okay from them. They're okay to be used. So you can go there, you can look at them. Some of the things to really note about their profiles are the level of description that they provide in their previous jobs. They also provide things like their licenses and their certifications. So they took little UX courses and they put that in there. They took project management courses and they put the certificate that you get in there. And hiring managers and team members that you're gonna be working with, they're probably gonna look you up on LinkedIn and they're gonna see these things and they're gonna say, oh, okay, this person is serious. They've done these courses, they have these skills. They've been endorsed for these particular things. And then again, reach out to those contacts, those friends, acquaintances, friends of friends and ask them, do the informational interview. I guess I heard the very end of that that might be a US specific thing, but it sounds like, from my experience, looking for jobs in the US, everybody that I've reached out to has been totally willing to do 20 minute, well, in person chat or over Zoom, no big deal and really the worst case scenario is that they don't respond and there's really not much to lose. Most people are really happy to help, actually. So, all right, and the best case, they can hand your resume right to a recruiter, which is really the best case scenario. Cool, so I am over time, thank you so much and we can do questions now. Thank you so much, Kelsey. I was keeping track of some questions I wanted to highlight for you, please. Cool. And as we go through, also, you can feel free to raise your hand non-verbally, raise your digital hand and we'll call on you. You can also just unmute. So, one question was about timeline because timeline in the industries that support these kinds of positions is very different from academia, which is very different from federal job hiring. So, what's the timeline? If you graduate, for example, in summer 2022, what would be a good time to start submitting applications? That's a really good question. Unfortunately, it kind of depends on the company, but I would say probably three to four months before you want to have the position start applying for the position. Of course, you're probably not gonna get, you're probably not gonna hear back from everybody that you apply to. And some people are faster than others. So, a couple of just anecdotal experiences. So, contractors tend to get back to you much quicker. They tend to have a higher immediate need. So, getting a contract position probably the quickest way to get into this. There's kind of some debate as to whether getting a contracting position will then be able to launch you into a full-time position if that's what you're looking for, but we'll put that aside. For Amazon, they're actually really quick. So, when I interviewed for Amazon, I submitted my resume at the end of November. I got a call back in December and then interviewed the first week of January and started the second week of February. So, that was really a little unlike all things told between when I applied and when I got the job was just a little bit under three months. And then started a little bit later than that. I have also heard of people at Google where their job process has gone on for six, seven months because they kind of hire for the role and if there's no role filled, but you've gotten the role, then you can kind of just be in this limbo phase until that role opens up again. So, sorry, go ahead, Alex. No, thank you, Kelsey. I just wanna, thanks for talking about the variation in timeline. One thing I wanna differentiate is sort of your active job search time and everything that precedes that. And really what you wanna be doing starting now is investing time in building out your network, which is what is gonna pay off later when you are in the active phase of applying for your jobs because- Exactly. What networking does and what informational interviewing does, that is your research project and that will help you hone the areas, the sectors and the types of jobs that may be a good fit for you. So what you wanna avoid doing is end of fall semester, beginning of spring semester before you graduate. You wanna avoid suddenly starting then and like, what am I gonna do? What's a good fit for me? Invest time now during this month. This is what we're here for in building out your network and learning about different positions, learning about different levels of positions, day to day life, that's what's gonna pay off later when you search for announcements. You'll have that knowledge in the back of your brain about what organizations you wanna target, what sectors of right fit, who can look over your resume for you. And so you're in the right place to start now looking for those jobs. And I know there's a hand up that we had one question further back that was duplicated about what tech skills should we learn and where should we start? That's a really good question. I think that that really depends on what kind of job you're looking for. So if you're looking for a position that is in the natural language understanding, natural language processing realm, a really good place to start is actually Draftske and Martin's Speech and Language Processing book. It gives a really great overview written bilingualist, so in language that we understand, of just what goes into building a voice assistant basically, building speech processing models, building language processing models. From there then, they do have some exercises and assignments that you can assign yourself. And from there you can kind of see like, oh, are my Python skills good enough that I can just manipulate the things that are here for my own needs? Or do I need to do a little bit more focus study on how to manipulate things in Python? A really good thing is just knowing your way around the command line, if that's in your vision for the kind of job that you want in the future. And then just, yeah, basic familiarity with, I mean, even with like Excel data analysis. So can you look at a bunch of numbers and make sure that whether things are statistically significant? Can you look at, well, sorry, I had another train of thought at the same time. One thing that people are really interested in right now is inter-anitator agreement. So there's a lot of annotation that goes on and from different annotators. And so how can you be sure that we're getting good data from these annotators that you might have from, that you might know or that you might just have gotten through mechanical Turk. So those kinds of things are good, just as jumping off points. I do also have a couple of slides at the end of the presentation and an appendix with some links to other things as well. You know what, Kelsey, when you just raised this term that's new to me of inter-anitator agreement and that means addition and the type of work, this is an area which I think would relate to people who study applied linguistics and who focus on inter-rater reliability. Absolutely, yeah. And critical skill and that's an example of language you would want to adopt. You would want to look for that and you would want to adopt it in your own materials. Don't necessarily talk about yourself as having experience in inter-rater reliability. Talk instead about inter-anitator. Talk about, make that, draw that connection to that. Exactly, yeah. And I'll see, if you don't mind, there's a question getting a lot of track from your chat. What about if a job says they require five years of experience in the field but you meet all other requirements? I just saw this for a language engineer job at Amazon. How much do they care about work experience if you have a strong linguistic background? Like PhD? You should just apply anyway. That is my advice. Just apply anyway. A lot of these companies, they say that they want five years of experience but in a lot of cases, Alexa has only been around since 2014. So you'd have to have been working on Alexa since 2016 to have five years of experience in that position. So those are pretty flexible usually. And also, you know, you have, if you're in a MA program, a PhD program, count those years as experience. Those are years of linguistic experience. You are a linguistic professional, so count those years. There's one thing I wanna address. So Christina in the chat asks, was there really only one interview for Amazon? No, there was one phone interview and then there was a whole day of five interviews that was in person. So it was pretty rigorous, but the turnaround time for Amazon, scheduling those interviews was pretty, pretty small. And maybe, yes, if you're back, thank you for your life. Oh, hi. Thank you for all of this presentation. It's super informative and very useful. I'm wondering about switches between jobs. Like if you get a contractor job and then you want to switch to something better, but then you're afraid of offending people at your original position, like how do you deal with that? And when do you let people know that you're going to be sweet to the switching? That's a good question. So I think specifically between contractor positions and full-time positions, I think people are really understanding, especially in my experience, because they know that you're a contractor, this is a limited time that you're gonna be spending. They have to know that you're going to be looking for other opportunities while you're doing that. And so when I transitioned from being a contractor to being a full-time employee, I think it was the standard, I think I gave maybe two weeks notice, but then ended up, there was a project that I was kind of passionate about and really wanted to see to the end. So I ended up going for three weeks. But that was really, it was not as hard as you would have thought it would be. Then switching between full-time roles. In my experience, it was a bit difficult. Of course, the position that you're at doesn't wanna see you go, but it really is dependent on what you see for yourself as something that's gonna be what you want. And when I was at Amazon, I realized, this is not really the position that I want. It's not the thing that is working for me right now. And when I had that conversation with my manager at that time, he was sad to see me go. He wanted to try to get me to stay, but ultimately realized that it was the best decision for me. And I still do have good relationships with all the people that I've worked with at Amazon. So it's not, you don't wanna burn the bridge, obviously, but I think people are really understanding about that. Thanks for the question. I see Charlotte, I think you have your hand raised. Hello, thank you so much for your presentation. It was very interesting to see the overview of different jobs. So I wanted to ask a question that was asked in the chat by way. I think, and I don't think the question has been addressed, but if it has, I'm sorry. It was the question of citizenship. We started a Slack channel to have international people talk among each other to talk about visa processes. And so I think a lot of us would like to know what are their constraints in terms of citizenship and work permits in tech? If it's like, if you're like, I'm a student, I'm on a student visa right now and I can get an OPT visa after that. But then if I want to continue, I would have to have like an HB1 or something like that. And so if you know anything about the recruitment of people who are not citizens, thank you. Sure. No, I think that that's a really great point to bring up. And I think that at least from coworkers that I've had, it's not an easy process. But if you are the correct, if you're the right fit for the position and they're the person that they want, those employers are going to do whatever they can in their power to help you out with that. That doesn't necessarily mean that visa and immigration services are gonna be, that's not gonna be any easier than it is, but the company at least, if they're hiring you, they have your back on that. And I do know a couple of people who transitioned off of an OPT visa onto an HB1. There were a couple of hiccups. It was pretty stressful for her for a couple of weeks, but it did work and she's still employed and it's totally fine. I don't know the specifics, but I could ask my coworker who had a bit of a difficulty. So he started at one position and wanted to move to another job, but there were some restrictions on his visa that made it so that he really couldn't move to another job easily. I will get that information and I can maybe send it to either Alex or Emily and hopefully we'll have some info on that for you. And if I could follow up really quickly, we do have someone coming to office hours who will address this very thing, an international person who will talk about the challenges of being an international person, searching for jobs within the US and securing them. And we'll also address working abroad as well. So I'm gonna search with their name in the chat. For now, I wanna thank our presenter, Kelsey Crouse. Thank you so much for being with us today. Thank you for having me. It was great to talk to you all. And if you have any questions, feel free to reach out to me. Add me on LinkedIn, find me wherever send me an email. I'm super willing to talk to people to help more linguists get into tech.