davidmnoll
Remote: Open to remote / in person / hybrid
Resume: https://davidmnoll.github.io/assets/David_Noll-Resume-982cc7...
Front End: TypeScript, React, Vue, Redux, Prisma, Jest, Cypress Back End: Python, Node.js, Django, Flask, PHP; Some Scala, Haskell, Java, Rust AI: LLM Integrations, Clustering with Embeddings, prototyped semantic search DevOps: AWS, Azure, Docker, SQL, Linux; Some Terraform, Kubernetes, AWS CDK, Ansible
Software Developer with 10+ years full stack & infrastructure experience. Recent work also includes prototyping and exploring AI applications. Background in cognitive science with focus in cognitive linguistics.
Resume: https://davidmnoll.github.io/assets/DavidNoll-Resume-1d19078...
Core Skills: Python, Typescript/JS/Node.js, React, SQL, Postgres, PHP, Some Java, Some AI, LLM/GPT integrations
Experienced Full Stack Developer with early startup experience and broad background. Available to start immediately.
Remote: Open to remote / in person / hybrid
Resume: https://davidmnoll.github.io/assets/DavidNoll-Resume-1d19078...
Core Skills: Python, Typescript/JS/Node.js, React, SQL, Postgres, PHP, Java, Web3/blockchain, Django, LLM/GPT integrations
Developing Skills: Rust, Functional Programming, Haskell, Scala, C++, Solidity, Data science / statistics
Experienced Full Stack Developer with early startup experience and broad background. I have experience in many domains and am able to learn new domains quickly. I am available to start immediately.
Willing to relocate: Yes
Resume: https://davidmnoll.github.io/assets/pdf/DavidNoll-Resume.pdf
Email: [email protected]
Github: https://github.com/davidmnoll
Experienced full stack developer, looking for position in collaborative culture in a technical environment.
Front End: Typescript, React, Jest, Cypress
Back End: Python, Django, Flask, Node
DevOps: AWS, Docker, databases, CI, Terraform, Kubernetes
Remote: Yes
Willing to relocate: Yes
Email: [email protected]
Resume: https://davidmnoll.github.io/assets/DavidNoll-Resume-9d9913c... Github: https://github.com/davidmnoll
Experienced full stack developer, looking for position in collaborative culture with a strong team.
Previously lead engineer at NYC start-up. Led remote team of 3 other developers. Set up CI/CD pipeline & testing. Worked on problems around scaling, testing, maintainability, security as well as new feature delivery.
Pretty interesting stuff, I was considering taking a crack at it as part of a project I'm working on.
Edit: [here](https://franklinta.com/2014/10/19/serverless-webrtc-using-qr... the blog post about it
Remote: Yes
Willing to relocate: Yes
Resume: https://davidmnoll.github.io/assets/pdf/DavidNoll-Resume.pdf
Email: [email protected]
Github: https://github.com/davidmnoll
Experienced full stack developer, looking for position in collaborative culture with a strong team.
Previously lead engineer at NYC start-up. Led remote team of 3 other developers. Set up CI/CD pipeline & testing. Worked on problems around scaling, testing, maintainability, security as well as new feature delivery.
> Instead of blaming food deserts, lack of nutritional knowledge, lack of time to prepare meals, and so on, what if the blame went directly to the parents who are letting their elementary age children graze on a party sized bag of Doritos?
Most people who would be in any way affected by a society-level shame campaign already feel that way. You're talking about small pockets of communities that aren't fazed by mainstream society's norms. Mostly ones in small-town conservative areas that are heavily shame-based, but just about different things from what you care about.
So it seems it's not more shaming that you want, it's just that you want everyone to be shaming people in line with your personal system of morality.
Using the idea that millions of people are just morally deficient as public policy is a proven failure. There’s always a reason when millions of people are doing the “wrong” thing, and the job of public policy is to assess the return on investment to society of removing those reasons or otherwise disincentivizing the behavior.
Personal responsibility is a personal lesson that requires personal choices and experiences. It’s not something you can publicly mandate
With all the resources going to academia, how much of them are focused on understanding the behavior of organizations? It's a reasonably tractable problem that's way underdeveloped, and would allow us to design new institutions that behave the way we want, rather than being beholden to institutions that having to tolerate the ubiquity of organizations with outcomes antithetical to the goals of the members.
The first problem to focus on could be assessing the effect of a decade-long induction process to be considered qualified to make the most miniscule contribution to academia.
I feel like I've noticed academics getting more and more cloistered, many of them rabidly defensive, completely shunning anyone with the slightest criticism of the process, credentialed and not alike. I'm guessing it has to do with (a) the thinning out of public resources, so more competition, more consequences to being wrong, more emphasis on sounding right rather than being right. (b) the fact that in most fields, the point of diminishing returns has been reached on the foundational axioms that define the field. And yet, defining a new field with new foundational axioms is extremely difficult, with scarce resources to explore it.
You could readily define new kinds of mathematics with different axia. The hard part is building off of those axia to make useful theorems. Some axia might lend themselves more readily to proving one theorem versus another, or might make it easier to model one thing versus another. We can see this with ZFC versus category theory. Similarly, analyzing fluids in terms of laminar versus turbulent flow yields distinct benefits. They rely on models with different core assumption. At the foundation of every field (or subfield) is a model & set of core assumptions that allows work to be built on top of them. Market economics versus game theory is a good example. The two models hold fundamentally different assumptions. Game theory is studied in economics departments, though, so its full potential isn't tapped. Any results from game theory can't too directly contradict what's come from market economics if it wants to get taken seriously in an economics department. If game theory had developed as a branch of sociology instead, we might see a very different ideas coming from it. No matter what, it can only be developed in directions is can get funding for.
If we really want to get at the truth, for every assumption we make, we should also define and investigate a theory that has the opposite assumption. For instance particles are indistinguishable. Great, that has yielded immeasurable results. Now let's fully flesh out at least one model that assumes they are distinguishable and hammer results out of it until they meet experimental predictions, too. We will likely find that there are some situations it can describe much more richly than our current models. And, that way people aren't going around forgetting it was an assumption to begin with.
Remote: Yes
Willing to relocate: Yes
Resume: https://davidmnoll.github.io/assets/pdf/DavidNoll-Resume.pdf
Email: [email protected]
Github: https://github.com/davidmnoll
Experienced full stack developer, looking for position in collaborative culture with a strong team.
Previously lead engineer at NYC start-up (remote). Led remote team of 3 other developers. Set up CI/CD pipeline & testing, improved performance to allow 100x+ scaling of data, helping them deliver to fortune 500 customers. Worked on problems around scaling, testing, maintainability, security as well as new feature delivery.
I can give you an abundance of examples. We were creating a page that was going to use state in a certain way. I was trying to insist that we address the way state will be handled across pages ahead of time. These concerns were dismissed as premature optimization. A few months later we had 5 pages with the state being handled in 5 different ways, and being synced in different ways between each page, complete with if statements, sometimes passing state through URLs, sometimes through local storage, sometimes through session, sometimes through JWT data, generally through a combo of several of them. Then we'd end up with confusing redirect loops for certain edge cases, state getting overwritten, etc.. We spend weeks fixing these bugs, and, eventually, weeks refactoring to manage state in a simpler way. These bugs often got caught by customers, drawing us away from feature delivery that was critical for demos to large customers.
All of that could have been avoided by spending 1 day thinking a little harder and planning for the future.
It ultimately boils down to a couple assumption that people like to make. (1) engineers know nothing about the domain, they can never predict what will be needed. That might be true in a large company with obscure domain-specific things for engineers who work far away from the day-to-day, but sometimes the engineers know exactly what's going to come up. (2) You can hill-climb your way into optimal program implementation. You can get to local maxima this way, but there are regular ways that programs grow based on how the business is growing and you can predict certain places where you will soon hit diminishing returns for current implementations. As long as you're up front about it and double-check your assumptions about the way the business is growing (and hence the application), I think there are ample places where you actually are going to need it.
3 days later I deployed my “nice to have” fix and the performance issues disappeared.
I’ve also seen a company stall out scaling for years and lose multiple million-dollar customers despite having a novel in-demand, market leading product because they refused to do anything to clean up their infrastructure.
This mentality is often taken way too far. I had an old boss who wouldn’t allow me to write unit tests citing this thought process.
Even at places with decent engineering practices, I’ve seen so many examples of software where you’re limited to a one to many relationship for something that could and easily should have been implemented as many to many, rendering the product useless to many because a product person couldn’t stand to think a couple months ahead.
Some people seem to take this idea too far and basically assume that if a problem is interesting or takes away a tedious task, it must be overengineering, premature optimization, or an imaginary problem.
Perhaps a better way to phrase the issue would be “artificial constraints”, which would encompass the flip side too.
Remote: Yes
Willing to relocate: Yes
Resume: https://davidmnoll.github.io/assets/pdf/DavidNoll-Resume.pdf
Email: [email protected]
Github: https://github.com/davidmnoll
Experienced full stack developer, looking for position in collaborative culture with a strong team.
Previously lead engineer at NYC start-up. Led remote team of 3 other developers. Set up CI/CD pipeline & testing, improved performance to allow 100x+ scaling of data. Worked on problems around scaling, testing, maintainability, security as well as new feature delivery.
Basically I do a poll of something like (a) confidence that the solution will fix the problem (b) estimated 80% confidence time range required. I do that for whatever options have been proposed, and then use the information to determine which option is the most promising. There's some principle that the average of many guesses is better than one, so I try to use that to make a better decision.
Remote: Yes
Willing to relocate: Yes
Resume: https://davidmnoll.github.io/assets/pdf/DavidNoll-Resume.pdf
Email: [email protected]
Remote: Yes
Willing to relocate: Possibly
Technologies:
- Python, Django, PHP, JavaScript, SQL/RDBMS, React, Linux admin, Git
- Some: Node.js, TypeScript, Java, Redux, Vue(x), Functional Programming
LinkedIn: https://www.linkedin.com/in/nolldavid/
Resume: https://davidmnoll.github.io/assets/pdf/DavidNoll-Resume.pdf
Email: davidmnoll [at] gmail.com
Experienced full stack developer, looking for position with room for growth in collaborative culture. Was previously first full time employee at bay area start-up, helped them grow to 5+ developers & 15+ employees, working on problems around scaling, security, reliability, legacy app maintenance, upgrades, etc.
Open to Contract & Full Time