Weights and Biases

San Francisco

51-200 employees

The future of machine learning - tools for experiment tracking, improved model performance, and results collaboration

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Customer Support Engineer, Machine Learning - LATAM

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Deep Learning Engineer

Weights and Biases

Deep Learning Engineer

ML Engineering

This job is no longer open

At Weights & Biases, our mission is to build the best tools for machine learning, and we’re hiring an experienced machine learning engineer to help improve our products and help us reach all the machine learning practitioners out there.

In this role, you will collaborate with across internal teams to create interesting machine learning projects and shape high quality tools and integrations that make other machine learning engineers' unlock their productivity.

You will own the execution of campaigns that target Deep Learning researchers at universities & in the real world – to help them understand the unique value of our product stack.

Some of your day will be spent training interesting machine learning models with W&B and writing about them, some of your day will be spent integrating our platform into common deep learning platforms and designing and building visualizations, and some of your day will be spent running exciting initiatives in our community of over 5,000 ML engineers.

We love building powerful tools together, delighting our users, and being part of the evolution of this exciting space. If you are passionate about improvement and experimentation, we encourage you to apply!

Responsibilities

Improving our integrations with deep learning frameworks
Running interesting experiments and writing publicly about them
Creating and orchestrating fun machine learning challenges within our community
Engaging with academics and ML practitioners alike to understand their needs and create unique ML projects that inspire them to use W&B
Improving our core machine learning tools by contributing ideas and feedback

Requirements

A bachelors, masters, or PhD in computer science or a related field
Machine learning and programming experience in a professional or research setting
Deep experience with one of the major deep-learning frameworks (PyTorch, Tensorflow, Keras, etc.)
In-depth understanding of common machine learning techniques in vision, audio, and NLP.
Willingness to try things, learn from them and iterate quickly.
Work autonomously in a self-directed environment
Enjoy the fast paced environment of a startup
Great attention to detail
A proactive, kind, and collaborative mindset

Why join us?

Top-tier machine learning teams love and rely on our tools for their daily work at companies including OpenAI, Toyota Research Institute, Lyft, Samsung, and Pandora.
We have extensive experience working with companies to turn machine learning research projects into scalable, real-world deployments. We’ve watched hundreds of teams struggle to deploy machine learning models successfully, and the same problems show up repeatedly. Machine learning has created a fundamentally new kind of programming, requiring a fundamentally new set of developer tools. We created Weights & Biases to provide that missing toolkit.
Our user base is growing rapidly.
We have raised significant capital, but the team is still small and there is the room and resources to make a big impact.
Here's a quote from Wojciech Zaremba, Cofounder and Robotics Lead, OpenAI: "W&B allows to scale up insights from a single researcher to the entire team, and from a single machine to hundreds of them."
Our stack: React, Typescript, GraphQL, Python, Golang, Kubernetes, Google Cloud Platform
You'll never stop learning. This role gives you first-hand experience talking to industry leaders and showcasing real-world applications of machine learning.

We care about diversity and are seeking people who love to learn and collaborate in an inclusive environment. We are an equal opportunity employer and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

This job is no longer open