Verse Medical | Full Stack Software Engineer | NYC preferred, remote (US or Canada) also works | Series A startup
It costs nearly $12,000 a night to spend a night at the hospital in the US. We're building software that allows patients to recover at home sooner and with better results. We're backed by top investors in technology & healthcare (e.g. Y Combinator, SignalFire, Paul Graham, etc.)
We have a product & engineering focused culture with minimal bureaucracy. We use Python and Typescript with GraphQL to tie it together. But, we're confident good engineers can learn new technologies so we don't require any particular language/framework background.
We're growing fast, are well-capitalized and growing our engineering team!
Hiring across a range of experience levels (new grad to staff). Email dhaivat AT versemedical.com to apply.
Please correct me if wrong, but these are likely measured via the book value of the investments which reflects the private market valuations of the companies you mentioned.
The target market for Google Hire was probably Lever's (https://www.lever.co) customers, i.e. mostly funded startups and other companies hiring white collar employees. For these businesses, $200-400/month for an Applicant Tracking System is pretty inline with market. Lever's pricing is higher as far as I've seen.
As someone working in this area, this is an interesting article.
The core issue of compliance is somewhat buried in the text, but worth pointing out. Optometrists' chief complaint is that very few offices seem to be prescribing the Hubble contacts brand specifically and yet, Hubble seem to be selling them to customers. This implies to them that either all prescriptions aren't being verified or are somehow being "passively" verified. Within the current rules set in place by the FTC, they believe it's unlikely quite so many prescriptions are passively verified.
The FTC is actually actively working on developing new rules around prescription verification to address some of these concerns. [1]
You could make this same argument to argue that Slack would fail against email.
Something like: there are all kinds of email integrations, user-specific and group-specific setups, etc. at companies. How can Slack ever compete?
The answer was that Slack was so much better for many companies that it made sense to suffer the pain of switching.
The company that beats Slack will likely be 10x better communication software or something very similar but distributed much more effectively (maybe Microsoft Teams in the enterprise).
On the flipside: if you're a person that's convinced Uber should be valued at a fraction of what it is and you're not shorting it, why aren't you?
You might argue the market will remain irrational, but this is unlikely to be the case for 25+ years. This should mean that most people set against the Uber IPO should hold a short position with at least a small portion of their net worth. Doesn't seem like this is the case.
Whether or not a company is a "tech" company is kind of a muddled question, but taking even a brief glance at https://airbnb.io/ (their engineering blog) makes it clear that AirBnB does some pretty serious engineering.
For example, their post about their work in search ranking is quite interesting [1].
Not meant as a critique to this book, but the fact that RL-based approaches rarely work for optimal control problems (in, for example, robotics) came as a surprise to me, given the hype and focus on RL [1]. It turns out that model-based methods for optimal control (e.g. linear quadratic control) invented quite a long time ago dramatically outperform RL-based approaches in most tasks and require multiple orders of magnitude less computational resources. Maybe there's some hope for RL method if they "course correct" for simpler control methods. At the moment, it seems like RL for robotics and control lies to the side of "research" and not "engineering."
Apple Music, et al. license content and there are few companies that are able to do this. This creates a barrier to entry that wasn't present for the "content clubs" Gates discusses. In fact, his primary point is that due to the lack of a barrier to entry in the market and no accumulating advantage of any kind, there wouldn't be a single dominant player.
One of the keywords you're looking for is "statistical forecasting."
It's a fairly specialized data science skill since it requires experience with some fairly specific techniques (e.g. dealing with seasonality, autocorrelation, etc. within data has all kinds of interesting solutions).
> Where did you guys get that idea that prescription should match so very precisely?
It's often much less about the prescription than the characteristics of the material used for the contact lenses and the measurements of your eye. The base curve and diameter portions of the prescription are used to capture this.
> Why do you need a specially trained person to dispense a box of contact lenses?
There are two reasons. With the wrong set of contact lenses (e.g. off-prescription color contact lenses that people wear on Halloween), you can significantly harm your eyes due to low oxygen permeability in the lenses, lack of fit, etc. Second, the contact lens/glasses prescription renewal process forces people to get an eye checkup done, which can often allow the doctor to identify other problems (e.g. infection, cataract, etc.)
It's subjective whether or not using this as a forcing function is really the "right" thing to do, but it does prevent people from living with undiagnosed issues.
> Also, what's the deal with vision insurance?
As people get older, the likelihood of an eye issue increases dramatically. This depends on your specific policy and what it covers, but there are "insurable" (i.e. low likelihood of occurrence, very high cost) events that can occur with your eyes that your VSP policy may cover. I'm not deeply familiar with this, so I can't comment extensively on it.
Essentially, the problem (like all other ad opt. problems) boils down to estimating the expected value of a particular click. This is a particularly challenging/weird problem in this space because unlike other segments of ecommerce, you can't successfully optimize for correlated metrics such as engagement. So, it's a heavily imbalanced problem (i.e. few positive examples, lots of negative examples). In addition to that, the buying characteristics of specific products are heavily related to one another so sales on one affect how we advertise the other. There are a number of other subtleties discovered over time.
Our software produces good bid estimates despite these characteristics.
That sounds interesting, but if you've been prescribed the Acuvue Moist, you can only purchase the Acuvue Moist as per law. So, although this info would certainly be interesting (and maybe reduce some customer confusion), it wouldn't actually be actionable.
We're transitioning to a new website ( which is already live on mobile devices when you go to https://beta.jetlenses.com/ ) . It's probably order of magnitude better and the logo is rendered as an SVG :)
Interesting point. We currently direct a lot of our customers to Opternative (https://www.opternative.com/) to renew their prescription. Medium term, we might look into doing some of this in house.
It costs nearly $12,000 a night to spend a night at the hospital in the US. We're building software that allows patients to recover at home sooner and with better results. We're backed by top investors in technology & healthcare (e.g. Y Combinator, SignalFire, Paul Graham, etc.)
We have a product & engineering focused culture with minimal bureaucracy. We use Python and Typescript with GraphQL to tie it together. But, we're confident good engineers can learn new technologies so we don't require any particular language/framework background.
We're growing fast, are well-capitalized and growing our engineering team!
Hiring across a range of experience levels (new grad to staff). Email dhaivat AT versemedical.com to apply.