Weights & Biases
Data AI · ML experiment tracking
Data AI · ML experiment tracking
Weights & Biases currently has 47 active AI-related job listings. The majority of these roles, 51%, are focused on serving infrastructure, with an additional 34% dedicated to agents. Engineering is the primary function being hired for, with the United States being the dominant hiring country. The company is frequently seeking candidates with experience in model serving, inference infrastructure, and LLM observability. Over the last 30 days, there has been a 75% decrease in new AI roles posted, with 4 new positions compared to 16 in the preceding 30-day period.
Currently tracking 35 active AI roles, down 14% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $92k–$341k (avg $211k).
Weights & Biases currently has 45 active AI-related roles in our index. The most common open titles are: Account Solution Architect (5), Account Solutions Architect - Greenfield (2), Account Solution Architect - Financial Services, Applied AI Engineer, Inference, Forward Deployed Engineer, AI Agents. Most positions are in Engineering and Product.
Weights & Biases's active AI hiring is concentrated in: serving infrastructure (51%), agents (38%), application (4%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Weights & Biases is hiring AI talent in: United States (43 roles), United Kingdom (2 roles), Canada (1 role).
Job postings at Weights & Biases most frequently mention: GPU Computing, Kubernetes, Production ML Systems, ML Ops, Storage Systems.
In the past 30 days, Weights & Biases has posted 5 new AI-related roles. That is a -50% change versus the prior 30 days (10 → 5).
| Title | Stage | AI score |
|---|---|---|
| Account Solution Architect Account Solutions Architect for a financial services customer portfolio, focusing on AI/ML and LLM workloads on CoreWeave's cloud platform. Responsibilities include deepening platform adoption, designing end-to-end solutions, guiding customers on AI lifecycle, and resolving technical challenges. Requires Python proficiency, experience with deep learning models, LLM applications, and financial services customer engagement. | AgentPost-train | 7 |