Senior Software Engineer, ML Verticals

Overview

Core Weave, the AI Hyperscaler™, acquired Weights & Biases to create the most powerful end-to-end platform to develop, deploy, and iterate AI faster. Since 2017, Core Weave has operated a growing footprint of data centers covering every region of the US and across Europe, and was ranked as one of the TIME
100 most influential companies of 2024. By bringing together Core Weave’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 Core Weave, 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.

Reporting to the Engineering Manager for ML Verticals, you will help design and build new mechanisms in W&B that allow machine learning practitioners to analyze application-specific data across domains such as robotics, finance, and health/bio.

The ML Verticals team focuses on rapidly exploring and shipping new analysis workflows, often in problem spaces where the right abstractions, data models, and UX are still emerging. You’ll work closely with users to understand how they want to interrogate their data, then iterate on product experiences by shaping frontend interactions and the underlying data representations that make them possible.

This role is frontend-led, but explicitly end-to-end: you’ll move quickly across UX, APIs, and data models to turn early ideas into production features used by thousands of customers.

• Rapidly prototype, iterate, and ship new analysis workflows for ML verticals, balancing experimentation with long-term product quality
• Design frontend experiences in parallel with backend schemas and APIs, evolving data models as user needs become clearer
• Work across the stack to implement end-to-end features, including adding or modifying logging formats, APIs, and data access patterns
• Make pragmatic decisions about how user-logged data should be stored, queried, and rendered to support new analytical questions
• Collaborate closely with product, design, and customer-facing teams to validate ideas early and incorporate real user feedback
• Improve reliability, performance, and scalability when working with large, complex, or high-volume datasets
• Contribute clean, testable, and reusable code; participate in code reviews and help establish patterns that reduce one-off solutions

• 3–5+ years of experience building user-facing software, with a strong focus on frontend development
• Comfortable working across the stack, including backend services, APIs, and data models when product needs require it
• Experience working in ambiguous problem spaces where requirements, schemas, and abstractions evolve over time
• Strong product instincts and ability to reason from user goals to technical design decisions
• Familiarity with modern web technologies such as React, Type Script, and GraphQL
• Solid understanding of programming fundamentals and experience with at least one backend or systems language (e.g. Go, Python, Java, C++, JavaScript)
• Bias toward action, iteration, and learning through building, with the judgment to avoid over-engineering too early

• Experience evolving or…