Rad AI | Remote | US/Canada | Full-time | Engineering Manager
Rad AI is a SF based Series A Generative AI Radiology startup with a remote team, of about ~ 40 engineers and machine learning scientists. We are applying large language models and state-of-the-art machine learning to streamline repetitive tasks for radiologists, which yields substantial time savings, alleviates burnout, and creates more time to focus on patient care.
We're looking for a hands-on Engineering Manager experienced with Python, Typescript, and React to play a pivotal role in helping us scale and prioritize our engineering teams. This will be a 50% individual contributor role with the other 50% focusing on management, meaning we're looking for someone who is willing to dive into technical strategy and problems whenever needed.
Rad AI | Remote (US) | Full-time | Multiple Roles (VP of Engineering and Senior Software Engineers)
Rad AI is a SF based Series A Generative AI Radiology startup with a remote team, of about ~ 35 engineers and machine learning scientists. We are applying large language models and state-of-the-art machine learning to streamline repetitive tasks for radiologists, which yields substantial time savings, alleviates burnout, and creates more time to focus on patient care.
Senior Full Stack Engineers: We are seeking a handful of Senior Engineers experienced with Python, Typescript, and React to work on continuing to develop our 2nd product, Continuity and to help us build our 4th product line from the ground up.
VP of Engineering: We are seeking a dynamic and hands-on engineering leader to play a pivotal role in scaling our software and machine learning teams. The team consists of ~ 35 engineers, however, we have ambitious expansion plans in mind and we aim to double our engineering team within the next 12-18 months.
Software Engineer | REMOTE (US / CANADA) | Full time
Pre-launch healthcare tech startup, led by seasoned healthcare entrepreneurs, looking for the third engineer to join our team developing and deploying a Python & Javascript application.
* Strong Python engineering skills with a thorough understanding of the ecosystem and best practices.
* Ability to design and run production containerized applications in Kubernetes (GKE).
* Experience with healthcare protocols (DICOM, HL7) and developing software with healthcare regulatory and security requirements (HIPAA & HITRUST).
* Understanding of machine learning, particularly around deploying and scaling solutions.
Experienced generalist who can collaboratively work across the product spectrum with our team and early customers to deliver a new, high-quality product to market.
Position includes salary, stock options, & benefits.
Nuance Communications | Burlington, MA | REMOTE | Full Time
Nuance Communication's Healthcare group is looking for a Senior Full-stack Python Engineer to join the team building the Montage Search & Analytics product. Montage is a data science framework that allows clinicians, healthcare administrators, researchers, and analysts to ask complex questions about healthcare data and obtain answers that improve patient and financial outcomes. Contribute to both the backend Python application and frontend Javascript interface.
The position can be fully remote, as noted on the Apply Now page.
Commercial Aviation (per 100,000 flight hours): 0.022
General Aviation (per 100,000 flight hours): 1.11
Motor Vehicle: (per 100 million miles): 1.5
General Aviation (which Flytenow falls under) has a fatality rate 2 orders of magnitude greater than commercial airlines (Delta, Southwest, Skywest, etc)
What if I find 1.1 deaths per 100,000 flight hours to be a perfectly reasonable risk relative to the benefits I receive from using such a service? I can't make that decision for myself?
The reason the "Fatal Accident Rate" is so different is because when a jetliner crashes, dozens or hundreds of people die. So a single accident is very deadly.
No, you're mis-interpreting the data. The commercial aviation record is as low as it is in spite of the large number of people on board. So the chances of accidents in general aviation are many times higher for any given flight using the one or the other mode.
In other words - and to make it really simple - if you are given the choice of going with a commercial carrier or with a general aviation craft to the same destination in a single flight then you would do wise to take the commercial carrier.
You're correct in the narrow sense (a commercial flight is less likely to crash) but wrong on the big picture (a commercial flight is safer for passengers).
Here's the thing: we don't care about the number of crashed airplanes, we care about crashed people (the number of deaths). And the number of deaths is about the same per passenger mile flown.
Passengers are no safer in either form of flying, according to this source.
It's worth getting to the bottom here, but like 'jacquesm' I think you are misinterpreting the data.
And the number of deaths is about the same per passenger mile flown.
Deaths per passenger mile is indeed the relevant metric, but this is not the number which is equal. Instead, the deaths per airplane mile are about equal. Since the commercial flights tend to have many more passengers, the passenger miles denominator will be greater by this ratio.
From a passenger's perspective, commercial flights are thus safer than private planes by this same ratio. I don't think the linked article gives enough information to calculate the ratio of passenger miles for GA and commercial, but 50x seems like it would be in the ballpark.
Why would we care about the number of crashed people? You said it yourself, the number of deaths for commercial flight is higher because there are more people on board. If I'm on a plane, I don't care about how likely I am to be one of the people who died in airline crashes this year, I care about how likely it is that this plane is going to crash.
I understand it's not intuitive, but the statistics are clear: If you have 100 times more people on commercial flights, then the flights would have to be 100 times less likely to crash to have the same risk to each passenger.
Let's break this into two specific questions (assuming the source is correct):
1) How likely is it that a specific flight will crash?
Answer: it's more likely that a private flight will crash than a commercial flight.
2) How likely is it that I will die on a private vs commercial flight?
Answer: your likelihood of dying is the roughly the same for both private and commercial flights.
I'm not sure you're reading the replies here. Nobody is arguing that your likelihood of dying is significantly higher on a private flight. We're arguing that the thing you should care about is whether the specific flight that you are on will crash, which has a significantly higher likelihood in general aviation.
Nobody is arguing that your likelihood of dying is significantly higher on a private flight.
I might be wrong, but this is indeed what I am arguing, and I think 'jacquesm' is saying the same. 'nostromo' says your likelihood of dying is the roughly the same for both private and commercial flights, and I don't think this is true if the metric is getting from point A to point B without dying.
If my memory of previous research is correct, a passenger on a private plane has approximately the same risk per mile travelled as a passenger on a motorcycle[1], which is something much greater than the risk per passenger mile of a normal automobile, which is in turn something significantly riskier than traveling the same number of miles by a commercial jet.[2]
We're arguing that the thing you should care about is whether the specific flight that you are on will crash, which has a significantly higher likelihood in general aviation.
Yes, each flight you take in a private plane is significantly more likely to end in a crash than each flight you take on a commercial airline. Your chances of being killed if the plane is involved in an accident are greater in a private plane (fatalities per accident are greater on the commercial flight, but risk to each passenger is lower). Therefore, your chances of dying per flight taken are greater in private flight than in commercial aviation. Is this the same as what you are saying?
[1] Edit: Found a seeming good source at http://www.nianet.org/ODM/presentations/Overview%20SVO%20Ken..., page 8. Looks like I was slightly wrong to say that motorcycles and GA are comparable risks. If we trust their estimates, motorcycles are about 2x more dangerous per hour than GA, and 3x more dangerous per mile.
Keep in mind the context of this conversation is about regulation, not about individual decision making.
From an individual stand-point, you are correct: "will my flight crash?" is a question that the individual would ask. But from a regulatory stand-point, the question is, "what is the safest way to transport people?" and those questions are not the same statistically.
This is similar to Taleb's "black swans" conundrum. You're comparing likely events with small ramifications to unlikely events with large ramifications.
QUnit is used to test the Javascript that is shipped as part of Django. Any application specific tests can use any JS testing framework the developer desires.
Montage Healthcare Solutions, Philadelphia, New York, St. Louis - FULL-TIME, REMOTE
Python Software Developer: Using Python / Django to develop and support our medical NLP and analytics product. Startup with full benefits. Full description at http://montage.theresumator.com/
Rad AI is a SF based Series A Generative AI Radiology startup with a remote team, of about ~ 40 engineers and machine learning scientists. We are applying large language models and state-of-the-art machine learning to streamline repetitive tasks for radiologists, which yields substantial time savings, alleviates burnout, and creates more time to focus on patient care.
We're looking for a hands-on Engineering Manager experienced with Python, Typescript, and React to play a pivotal role in helping us scale and prioritize our engineering teams. This will be a 50% individual contributor role with the other 50% focusing on management, meaning we're looking for someone who is willing to dive into technical strategy and problems whenever needed.
To Apply: https://jobs.lever.co/radai/81da5c19-00bc-4f80-b2ab-8969a336...