Weights & Biases
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).
Data AI · ML experiment tracking
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 |
|---|---|---|
| VP of Product, Research and Training Infrastructure VP of Product for Research and Training Infrastructure at an AI cloud provider. This role owns the product strategy and engineering execution for services powering AI research labs, focusing on specialized orchestration, evaluation, and iteration tools for massive-scale pre-training and post-training. Key responsibilities include evolving orchestration tools (SUNK), developing automated training-based evaluation frameworks, and building infrastructure for RL/RLHF pipelines. Requires deep knowledge of HPC, distributed training, and supporting frontier model research. | PretrainPost-train | 9 |
| Principal Solution Specialist, Infrastructure This role focuses on bringing CoreWeave's AI developer services, such as MLOps platforms and LLM observability tools, to market. It involves defining commercial and technical strategies, driving adoption with early customers, and translating field insights into product roadmap requirements. The role requires deep expertise in the ML development lifecycle, LLM application patterns, and MLOps ecosystem, with a focus on experiment tracking, model lifecycle governance, and observability. |
| AgentEval Gate |
| 8 |
| Solution Specialist, AI Runtime Services This role focuses on bringing new AI runtime services, such as model serving and sandboxes, to market. It involves driving initial customer adoption, gathering feedback for the product roadmap, and enabling sales teams to position these services. The role requires deep expertise in AI runtime infrastructure, including serving frameworks, inference optimization, and execution isolation. | Serve | 7 |