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ekarulf

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Sr Principal Engineer @ Amazon. These opinions are my own and do not reflect my current, previous, or future employers.

Want to work with me? See https://www.amazon.jobs/en/landing_pages/principal-engineer-hiring

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I get IVIG 3x / week for a primary immune deficiency I’ve had since birth. For my dosage, it’s billed weekly at a rate of ~$32K of which my insurance company pays around ~$3K.

I hit my max out of pocket the first month of each year and the rest of the year is “free.”

I know that all the IVIG pharmaceutical companies offer a “I can’t afford this” option if you’re going out of pocket.

Good luck, it’s stressful to get but it’s a miracle blood product for those who need it.

Just in the event someone out there is looking to work on these types of problems, Amazon's Personalization teams are absolutely hiring.

Homepage: https://www.amazon.jobs/en/teams/personalization-and-recomme...

Applied Science: https://www.amazon.jobs/jobs/372996

Software Engineering: http://www.amazon.jobs/jobs/549950 http://www.amazon.jobs/jobs/402127 http://www.amazon.jobs/jobs/430623

Software Managers: http://www.amazon.jobs/jobs/385902 http://www.amazon.jobs/jobs/437405 http://www.amazon.jobs/jobs/489879

If one of those don't strike your fancy but you are passionate about working in this space, feel free to send me an email: ${HN_USERNAME}@amazon.com.

Who says they can't see the URL? A sufficiently motivate government would probably be able to create forged certificates and mass interception isn't really out of the question. Especially with browsers homogenizing on fast ciphers AES-GCM/POLY-1305, I bet it's much more economical than you would think.

Cert Pinning or HPKP is one type of solution, but it's tricky to get right especially for a large site like wikipedia.

I find it impossible to replace a legacy system without first understanding the legacy system. It's easy to say "X is old" or "X sucks at Y" but keep in mind that applications have a strong survivor bias. Ask yourself, "what does X do that is awesome" or "how has X lived this long" and you'll find a lot of hidden scars and requirements.

Start documenting those requirements and create a plan to map those to technologies that you prefer. Understanding how to successfully migrate platforms is a learned skill, and it's going to become useful again when React is no longer en vogue.

I'm a new parent and I need to track when my son eats/poops/pees etc. There are times when my hands aren't available. I built a tiny "app" that just records these things to a google spreadsheet for me.

I also like the idea of "authenticating" via being present in my home. If my in laws are watching my son while I step out for a few minutes - they can talk to Alexa as easily as I can.

It's a hard problem to determine the repeat purchase cadence of a product. At one end of the bell curve you have items re-purchased frequently, e.g. diapers or grocery, and on the other end you have items that are rarely repurchased.

I haven't looked at coffee tables specifically, but I know when I've looked at home products in the past I've been surprised at how frequently people will buy two large items, e.g. TVs or furniture, within a short period. That said, I agree there is room for improvement here. We're constantly running experiments to improve the customer experience, I have faith that in the limit things will improve. Again, we have no shortage of experimental power so if you'd like to join in the experimentation let me know :)

Amazon Personalization.

We use ML/Deep Learning for customer to product recommendations and product to product recommendations. For years we used only algorithms based on basic statistics but we've found places where the machine learned models out perform the simpler models.

Here is our blog post and related GitHub repo: https://aws.amazon.com/blogs/big-data/generating-recommendat... https://github.com/amznlabs/amazon-dsstne

If you are interested in this space, we're always hiring. Shoot me an email ($my_hn_username@amazon.com) or visit https://www.amazon.jobs/en/teams/personalization-and-recomme...

I was really hoping for an retrospective about a multi-armed bandit learning algorithm that ran in production but never experimented, effectively yielding a "zero-armed bandit".

For eight years of my life, I was this "Do-Everything Rockstar." I was also a student for the majority of that time. I certainly wasn't a "programming deity" -- I was just a kid that was presented with the opportunity to learn some incredible lessons about scaling, appsec, capacity planning, etc. I also learned soft skills like how to negotiate, travel, and delegate.

The skill set absolutely exists and, for the right person, it's a great job.

I wrote a similar system for C# - we had three queues per application, work, delay, and error. In our system, the deferred queue used per-message TTLs that would push messages back onto the work queue. This allowed us to inspect the deferred and error queues while the application was running.