Machine Learning Engineer

Los Angeles, CA /
Engineering /
Full Time (HQ)
Dispo aims to restore joy to the experience of photography. In fact, we aim to restore joy to modern life. We are not shocked that our love for the delight and surprise of disposable cameras is fun for everyone. A digital disposable camera experience allows us to reclaim our lives from our phones. Waiting for developed photos is like Christmas morning, and it allows us to use cameras to live in the moment and tell stories again. Our goal is to become the world’s home for photography’s ultimate purpose: storytelling and connection making.

Come join the team and live a little- or a lot.

-Team Dispo

What will you do?

    • Help build out our initial recommendation systems / modeling efforts and offline batch prediction .
    • Work with the broader engineering team to create our data pipelines and infrastructure.
    • Be responsible for roadmapping as well as make key architectural decisions.

Who are you?

    • Someone with experience working on production production recommendation or machine learning systems.
    • Knowledge of "classical" ml techniques and not just architectures from the latest n-billion parameter transformer models.
    • An engineer with product sensibility. We are a small team and product input comes from everyone.
    • Comfortable working from building basic data pipelines to prototyping in notebooks to serving in production.
    • Experience with Pytorch, Tensorflow, Jax 👀, or any modern and production capable ML framework.
    • You care deeply about performance and are comfortable analyzing model size and speed, datasets or whatever it takes to improve key metrics.
    • You can deal with multiple axes in challenging situations: scale, uncertainty, and speed.
    • Someone who wants to build an inclusive culture from day one.

Comp

    • Generous compensation
    • Generous vacation
    • Generous benefits
    • Generous food (Regy has a Costco card now, if that means anything to you)
    • Generous what else? You are an early employee. Just ask