Founding Fullstack Engineer | ZeroBroker | San Francisco | Remote possible

[long stream]

We’re looking for a full stack developer, ideally with Elixir experience and interest in AI. You’ll be instrumental in creating a new version of our product, but also responsible for keeping some legacy systems alive.

We are building the world's first AI logistics manager to help companies source, vet, get quotes, negotiate rates, and finalize bookings with carriers/vendors. We expect rapid growth in the next few months. The company was founded in 2017, went through YCombinator, raised a seed round in 2023. Using Elixir, JavaScript, and Python internally.

You will be responsible for building out our Elixir backend service as well as supporting an existing Node application. It’s important you’re comfortable taking on whatever work is necessary to complete a task 🙂 AI-based workflows are an integral part of our product so you’ll need either experience in building AI-based systems or are very interested in learning.

We’re a small team with big ambitions. Most of us are in San Francisco, but a couple of us are remote; we’re open to remote candidates, as long as you have a reasonable time overlap with US West Coast.

Send us your CV/LinkedIn/Github profile (whichever represents you best) to [e-mail] along with a short description of what you've done so far and why you're interested.

[devout oak]

Just thought I would double check, both in the interest of myself and possible future candidates:

You mentioned this requires experience with AI systems, but that’s a pretty broad topic. I would assume that you’re building a system based on NX (serving models directly from Elixir), potentially with some training, but the specific sub-field is probably pretty relevant.

Are you approaching this as a graph based exercise? Is symbolic AI planned to be useful here? Are you doing simple time series forecasting with RNNs? Time series VAEs? Are you considering the use of LLMs in any capacities (both in managing / retrieving data, or as an element of the user interface?). Are you dealing with small scale models deployable / trainable, on a single node or will it require experience with distributed systems at scale? Do you have any in house resources that are meant to be geared for (ie: in-house ARM / x86 CPUs, GPUs, specialized accelerators, etc), or is this all meant to be handled cloud side (and if so, do you have existing cloud infrastructure)? Is there an expectation that the dev hired will be handling scale out and MLops, on top of training / procurement and integration of models? Will an understanding of reinforcement learning be necessary? Are these questions the candidate is expected to answer as a potential technical lead who can solve the business problems with any of these solutions?

Sorry for the barrage of questions, but there’s a lot of nuance to modern machine learning experience, and answering at least a few these will probably help you filter towards the right candidate.