Teamworks | Multiple Senior and Principal engineering positions + an Engineering Manager position | REMOTE | Boston, Durham NC, Birmingham AL
About us: We are the operating system of elite athletics. We provide the software that supports your favorite sports teams, whether you're a fan of collegiate American sports, NFL, NHL, the NBA, New Zealand and Australian Rugby, or EPL football (and more!). We provide everything from messaging, calendar, forms, and compliance to nutrition management (via Notemeal) and branding (via INFLCR).
Responsibilities: depends on the position, but generally we're looking for people who want to flex between product and engineering.
I find ADHD to be an "occasional" disorder. I feel very much like the author much of the time, but honestly I want it to continue to be researched as a disorder, because I want strategies and medications that are better than post-it notes and Adderall (and yes, I've tried lots and no, none of them are better for me than the occasional 5mg of Adderall).
Most of the time, ADD works in my favor. But sometimes, (and NOT always due to "societal expectations") I need my brain to work differently than it does, and for those occasions the meds do wonders. But I truly hate the after-effects, thus I rarely take them.
I have family members with similar issues. If you could could elaborate, what are the common situations when ADD works in your favor, and what are the times when you find you need your brain to work differently?
1. When high levels of energy or reaction are required e.g. sports and games where reaction speed and/or impulsivity is advantageous. I have been told on multiple occasions when I have been in emergency situations with others, that I do not tend to "Freeze up" like many others do.
2. High stress environments -- When it gets down to "Fire and Brimstone" time, I can develop a "hyperfocus" in which I can focus for an exceptionally and unhealthy long amount of time. However, too much of this without recharging, and I burnout. In fact, I think there is a joke that ADHD medical school students all become ER doctors.
3. Environments where divergent and abstract thinking is beneficial over convergent thinking. I often think I can come up with good ideas, but I personally find my mind falling short of being able implement them.
4. Social situations. I know this somewhat ironic, since we tend to have trouble listening and pay attention to conversations, but I seriously have done extremely well in any role dealing with customer service, talking to unfamiliar people, etc.. I imagine a part of this is possible due to my personality, but I have heard anecdotes from other people with ADHD having similar experiences.
hirvi, this is brilliant and so relateable, so thank you. Mine are very similar, but I would add with respect to your points...
1. Yes, but I also have to know that I am the one in charge... otherwise I will not take charge, but I will be ready to be told exactly what to do, and THAT I will do very quickly. [see A below]
2. Also yes, and true for software development too, but it makes the long burn so difficult. Give me a fire to put out! I casually know an ER doctor who is highly regarded, but his personal life is a mess and he's into extreme sports. (And saw my son when he came in with a suspected neck fracture.)
3. Again, yes. Once a solution has been found, I'm done! Implementing it? Naaah... that's the boring stuff.
4. Sort of... I think due to personality and temperament yes, but also upbringing.
Two more points building on those.
Autism and adhd have a high co-morbidity. If someone has social skills to the point where others comment on how good they are; highly unlikely that's you. If the idea that you "intellectualise social interaction" rings a bell, it might be the case.
Sensitivity issues. This is a reason behind my addition to point 1 above. The most mild of corrections comes across as an accusation that one is am totally worthless and useless. A constant running inner critic devaluing every thought and action. My experience is that this is silenced or at least turned down by medicating with stimulants... and it is totally liberating.
Thank you, and I greatly appreciate your comment as well.
1. I can sympathize.
2. I am software engineer that has and currently played various extreme sports, so there is probably a strong correlation lol.
3. I don't have enough bandwidth to implement thing sometimes when the RAM is maxed out and I do not have any Swap Space.
4. Makes sense. My family was predominantly in the medical field and they constantly would have to talk with lonely and/or bored patients all the time. So, you are probably on to something.
> "intellectualise social interaction" rings a bell
I tried to search for what this meant, but I found a few differing ideas that I didn't know which one to attribute to what you meant. Do you mind elaborating?
I do tend to talk fast and talk a lot. It used to get me in a lot of trouble in school growing up because I would basically talk non-stop (wasn't diagnosed or treated during those times). I still talk a lot, but I have grown out of a lot of it.
I have sound sensitivity issues like misphonia and I hate going to concerts despite being a musician at one time due to how painful I find the volume. If I go, I have to wear earplugs or I find it physically painful to be a setting that loud. Same thing with small engine devices like chainsaws and other machinery.
I do not think I have co-morbid Autism, but if I do not, then I probably missed a good chance -- then again, there is probably symptom overlaps between the two.
3. Yes, that too. It becomes burn-out at the worst.
>> "intellectualise social interaction" rings a bell
> I tried to search for what this meant, but I found a few differing ideas that I didn't know which one to attribute to what you meant. Do you mind elaborating?
That was the goal behind me asking... if it did ring a bell; I think you'd know! I pre-plan social interactions, they inevitably never go as planned, then I spend forever ruminating on what I did wrong. Rinse, repeat.
To your concluding paragraph, I think a way to join back up these disparate threads is a reminder that ADHD and autism are both non-binary, spectrum conditions... they're labels slapped on a grab bag of manifested difference->disorder->disability symptoms, hence diagnostic criteria that are: "has to have 5 out of 8 of these factors".
Thanks for your examples, a lot of that really hits home, especially the stimulants. I have been trying to figure out why I can't quite function without caffeine, not in a get a headache and feel sleepy sort of way, but that without it I feel really listless and almost depressed.
This is absolutely correct. Neither chanterelles nor puffballs are "foolproof" mushrooms, even slightly. Mistaken puffballs are probably the number one cause of serious mushroom poisonings and even fatalities, since small puffballs look so much like amanita mushrooms that haven't fully opened yet.
And chanterelles have a number of at least moderately toxic lookalikes depending on the region you're in and how much an eager amateur is willing to stretch the definition. I don't think a lot of beginners can reliably tell the difference between "gills" and "folds."
Plus what you referred to about toxins leached from the tree that the mushroom was growing on. I'd not eat anything growing on a locust tree or a fallen rhododendron. Just seems like inviting trouble.
I think the "depending on the region you're in" part is what struck me most as lacking about this article.
It's also imprecise in giving advice on precise growing conditions. E.g telling a beginner that no matter what they think, a given mushroom doesn't grow in summer is a good way of reducing misidentification.
Yes, once you have felt and identified a chanterelle with success a few times, it's very easy for an experienced forager to tell the difference between gills and folds (especially in the larger species such as C. californicus). The folds are often veiny and cannot be moved or 'plucked' like gills. In general though, identification should be done using as many factors as possible (e.g. using a identification key which is like a decision tree). For example, besides gills and smell, another way to differentiate the (non- or only mildly-toxic) false chanterelle is the firmness.
Neither is a bad option, but there's plenty of room in between. Series B, C, are often still pretty collegial, and you'll still get the opportunity to know the founders. The market's really gung-ho right now, and wherever you go you should interview them as much as they interview you. Pick something that feels good and will let you breathe. It could be really tempting to be ambitious right now and the main advice I would give you is "don't."
Don't try to make up for lost time. Don't try to prove anything. Don't make the next thing anything more than what it is: a job. Once you've rested and recuperated, and you can look back on your time at your startup and not "cringe" or feel angry, then decide whether you want to lean into the job you're at or move on and be ambitious somewhere else.
I've been a co-founder at something that felt like a "zombie startup." I walked away, gave up my entire stake in it back to the other co-founders, and washed my hands of it. It's doing fine now, and I'm fine with that. I saved myself the three or more years of pain, heartache, and panic attacks, and hopefully I gave them the breathing room they needed to get the thing off the ground. I will never see a dime of profit from it, even if it becomes a unicorn, and I'm completely fine with that.
The thing I think a lot of co-founders feel after a startup fails is a sense of "purposelessness," Burnout that manifests itself as a feeling that you're not "smart" anymore, not "creative" anymore. A blank space in your day fills itself with wondering if you could have made it work if you'd just done that one thing differently. You can't "power through" those feelings. You have to let yourself live with them until they pass over you. You have to let yourself heal, and healing takes time. Whatever job you take now should let you focus on that. It needs to be something that lets you spend some mental energy working through the regret, frustration, and ultimately the fear of facing your part in the failure of the startup.
Do the job instead of "be" the job. At least for a while. Take the time and get past all the things that will stop you from really learning from your experience. Then at the end of that, if you still feel the burn to start something again, you'll be able to put your whole self into it.
You can use SSH keys for VNC, too. Would be neat to see a PoC that allowed you to invite someone to remote control your computer temporarily via their github handle. https://ubuntuforums.org/showthread.php?t=383053
You know, I really should add a post soon about algorithms, papers, and textbooks. You make an important point which the first responder highlighted, "avoiding the destruction of business value by misapplying ML/statistics."
I understand the math behind what I do, but it's not a fair assumption to think that everyone reading my post will be motivated to pick up and understand the math before they start applying the tools.
Especially with tools like scikit-learn and orange, it's especially easy to misapply ML and statistics or simply approach a problem without understanding the tools and come out with something that looks plausible to the untrained eye.
Key to the reason that you should understand your tools, including the math that underlies them, is that you should be able to look at the results of your work and know if there's something "off". And beyond that the underlying understanding of the math involved gives you the tools you need to debug.
I knew I was forgetting packages. I do in fact use Tableau. Will add it. Thanks for the catch!
As for LaTeX, it would have never occurred to me to add it. I have no idea why not, but it doesn't. Maybe because it feels more like a chore than a tool. It's like an anti-tool. I mean, I do or did in the recent past use LaTeX, but in more recent years I would farm that out to someone junior to me who hadn't worked with it for long enough to prefer pouring bleach in their ears to being faced with tweaking one more broken LaTeX template.
I probably should include classical stats packages. They really should go in here. But I've been coding since I was a kid and typically eschewed classical stats and math packages because of my perception that they were slow walled-gardens, and that as soon as I had a method figured out in Matlab or SPSS I'd end up rewriting it in C, C++, or Java to make it work with other things or at scale. That was hammered home in the first company I worked with where we did modeling in SAS and then rewrote every model in Java because SAS couldn't keep up.
I'm not suggesting that classical stats packages aren't data scientists tools. I think they are. They're just not my tools because of the curious niche I found myself in.
I think my job is similar to yours. My background is in engineering at an industrial manufacturing plant.
I have some of the same issues. The Engineers here tend to reach for spreadsheets first (or Access databases - these things are everywhere at my work) and inevitably they run into scaling problems and end up with a huge bloated mess. I step in to re-architecture these monstrosities (using "real" databases when necessary).
The other big part of my day to day work is modelling and data analysis. Usually regression based stuff and LP optimization problems (SAS is very good for this) especially around yield and quality control. The venerable excel "solver" plugin is often abused very heavily by engineers and is not always the ideal solution.
The person who I took over from was a Stats guy and the original job title was "Process Statistician" my boss has since retitled my role "Data Management Engineer". I still think of myself as an engineer first and foremost and a "data" person second.
I use SAS heavily. We have kind of gone in the opposite direction to you. I have rewritten some of our models in the past from C++ into SAS mostly for ease of maintenance because SAS is better understood by the non programmers (Most of the Engineers here do not have a programming/CS background and those that do tend to either know Fortran or Visual Basic very few grasp C/C++ very well). Speed is not really any issue but opaqueness and ease of maintanece is.
I'd like to learn R because I have heard it is very similar to SAS but more transferable to outside companies. Julia is the other language I've got my eye on I have heard it is somewhat similar to MATLAB which is used for some modelling work here.
sometimes i write python packages to auto populate tex files. like imagine running LDA with 50 topics and showing how each topic (via word cloud) correlates to an outcome variable
I think it's great that students and young professors in the sciences are taught to code now. I've even taught some of them.
To me, data science is more than understanding statistics, it's been essential to know how to scale them up and out.
If you're a domain scientist, you won't necessarily learn how to write reusable tools that are performant (or runnable) on data that is different from your initial model data. I once worked with a group whose model had grown so unwieldy that their config file was in NetCDF.
I found my niche was often in doing things that were slightly (or completely) outside the comfort zone of most domain scientists who were competent coders themselves, but who didn't have the funded time nor the inclination to learn things like database, visualization, and networking technologies that became necessary either to share their work with other research groups or to operate on larger datasets.
One project had me take a big model that was normally run twice a day and on a 4km grid and help write something that could run and visualize the results of the same thing on a 0.5km grid over a larger area and hourly. And then devise something that could help them visually explore the timeseries as it evolved, sometimes over months.
Designing the pipeline that can handle that is outside the scope of most scientists, even the ones who are good coders.
That line you're talking about sounds more like the traditional science/engineering divide. Maybe staticians are data scientists, but what we call "data science" is really data engineering?
Not all RESTful APIs will fit into a framework like this, and the choice of RethinkDB limits its applicability to a narrower community, but I intend on supporting other document-based DBs in the future. I really like RethinkDB's API and ReQL in particular, and it seems like a solid foundation to build something a little out of the ordinary on.
What makes it different from other ORMs? It's a rethinking of ORM mechanics for a "document-based" backend system.
* It tries to make the exposure of non-CRUD operations relate as a method to a logical server-side object and have a consistent endpoint syntax. It also uses Python function annotations to generate request and response schemas for methods.
All API endpoints exist within a four-tiered path hierarchy of
* Suite - base level, serves as a collection of applications and repo for basic shared schemas
* Application - a bundle of collections representing a logical set of functionality, methods that bind at this level act like "library functions"
* Collection - a collection of documents sharing a common schema. Methods that bind at this level act like "class methods"
* Document - a single instance of a document schema, representing concrete data. Methods that bind at this level act like "instance methods" in traditional OO programming.
What helper features does it have?
* Reusable apps / collections.
* JWT based sample authentication app, auth.
* Automatically generated help from schema descriptions and python docstrings
* Self-describing schema endpoints for suites, applications, collections, documents, and their methods.
This is pre-release stuff, to be sure. I'm using it on personal projects, but it needs:
* More tests
* More docs for the Python side of things (I'm working on this first)
The second line like the density of rods/cones in the retina. Also looks a lot like a space filling curve. In short this looks like it could make an interesting data structure...
About us: We are the operating system of elite athletics. We provide the software that supports your favorite sports teams, whether you're a fan of collegiate American sports, NFL, NHL, the NBA, New Zealand and Australian Rugby, or EPL football (and more!). We provide everything from messaging, calendar, forms, and compliance to nutrition management (via Notemeal) and branding (via INFLCR).
Responsibilities: depends on the position, but generally we're looking for people who want to flex between product and engineering.
All our open positions with links to apply: https://www.teamworks.com/company
If you want to read a little bit more about engineering at Teamworks, try these blog posts:
- What Software Engineers and Olympians have in Common: https://tw-engineering.webflow.io/post/what-software-enginee...
- You're Probably Doing Epics Wrong: https://tw-engineering.webflow.io/post/youre-probably-doing-...
- Technical Debt at Teamworks: https://tw-engineering.webflow.io/post/technical-debt-at-tea...