Software Engineer, Workspaces - Weights & Biases at Weights & Biases

About the role

CoreWeave, the AI Hyperscaler™, acquired Weights & Biases to create the most powerful end-to-end platform to develop, deploy, and iterate AI faster. Since 2017, CoreWeave has operated a growing footprint of data centers covering every region of the US and across Europe, and was ranked as one of the TIME100 most influential companies of 2024. By bringing together CoreWeave’s industry-leading cloud infrastructure with the best-in-class tools AI practitioners know and love from Weights & Biases, we’re setting a new standard for how AI is built, trained, and scaled.

The integration of our teams and technologies is accelerating our shared mission: to empower developers with the tools and infrastructure they need to push the boundaries of what AI can do. From experiment tracking and model optimization to high-performance training clusters, agent building, and inference at scale, we’re combining forces to serve the full AI lifecycle — all in one seamless platform.

Weights & Biases has long been trusted by over 1,500 organizations — including AstraZeneca, Canva, Cohere, OpenAI, Meta, Snowflake, Square,Toyota, and Wayve — to build better models, AI agents and applications. Now, as part of CoreWeave, that impact is amplified across a broader ecosystem of AI innovators, researchers, and enterprises.

As we unite under one vision, we’re looking for bold thinkers and agile builders who are excited to shape the future of AI alongside us. If you're passionate about solving complex problems at the intersection of software, hardware, and AI, there's never been a more exciting time to join our team.

What You’ll Do

Reporting to the Engineering Manager for Workspaces, you’ll join a collaborative team responsible for delivering end-to-end product features within our Models product—the central hub for experiment tracking and visualization.

Thousands of Machine Learning Engineers rely on our tools every day to monitor and understand their ML training runs. To see the kind of work you’ll contribute to, check out an example workspace or try our tutorial. The Colab notebook requires no prior ML experience to run, and we’re proud of how easy it is to get started.

About the Role

This role sits within our Models Engineering organization, where we focus on building features that streamline and centralize the machine learning development workflow. As a Product Software Engineer, you’ll work directly with customers and cross-functional teams to build experiences that accelerate ML model development.

You will:

Contribute to new product initiatives that help our customers (ML engineers) analyze and share information
Work closely with senior developers to tackle technical challenges and improve system performance
Help improve team productivity by sharing ideas, improving documen

Skills & Tags

react python java typescript javascript go rust aws

Aplyr's read

Weights & Biases is a hub for AI enthusiasts, offering cutting-edge tools for seamless machine learning development and collaboration.
Synthesized from recent postings & public sources

What's promising

•Strong focus on enhancing productivity for machine learning practitioners.
•Offers comprehensive tools for experiment tracking and model optimization.
•Highly valued by data scientists for improving workflow efficiency.

What to watch

•Limited public information about company culture and work-life balance.
•Potentially high pressure due to rapid AI industry changes.
•Niche focus may limit appeal to broader tech professionals.

Why Weights & Biases

•Specializes in tools specifically designed for machine learning workflows.
•Emphasizes collaboration among data scientists and engineers.
•Provides a platform that integrates seamlessly with popular ML frameworks.

Aplyr’s read is generated by AI from public sources. Was it useful?

About Weights & Biases

Weights & Biases

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Weights & Biases is a leading platform for machine learning practitioners, providing tools for experiment tracking, model optimization, and collaboration. Their solutions empower data scientists and engineers to streamline their workflows and improve productivity in developing AI models.