Abridge
Vertical AI · Medical AI scribing
- HQ
- Pittsburgh, US
- Founded
- 2018
- Website
- abridge.com
Vertical AI · Medical AI scribing
Abridge currently has 24 active AI-related job listings. The majority of these roles are focused on serving infrastructure, accounting for 33% of the openings, followed by application development at 21% and evaluation at 17%. Engineering is the most frequent function, with 14 roles, and all hiring is concentrated in the United States. The company is frequently seeking candidates with experience in model serving, evals, and llm observability. Over the last 30 days, Abridge has added 6 new AI roles, representing a 20% increase compared to the previous 30-day period.
Currently tracking 13 active AI roles, with 18 new openings in the last 4 weeks. Primary focus: Eval Gate · Product.
Abridge currently has 20 active AI-related roles in our index. The most common open titles are: AI Enablement Program Manager , Clinician Scientist, Data Engineer, Director, Data Science, Director, Product Management - AI/ML, Core Product. Most positions are in Engineering and Product.
Abridge's active AI hiring is concentrated in: serving infrastructure (30%), agents (25%), evaluation (20%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Abridge is hiring AI talent in: United States (20 roles).
Job postings at Abridge most frequently reference: llm observability, evals, model serving, agent orchestration, inference infra.
In the past 30 days, Abridge has posted 4 new AI-related roles. That is a -33% change versus the prior 30 days (6 → 4).
| Title | Stage | AI score |
|---|---|---|
| Engineering Manager, Model Inference Engineering Manager to lead and grow the Model Inference team, focusing on architecting and scaling low-latency, high-throughput inference infrastructure for Abridge's generative AI products in healthcare. Responsibilities include technical direction, model optimization, deployment, and team leadership. | Serve | 9 |
| Machine Learning Infrastructure Engineer- Model Inference This role focuses on building and optimizing the core inference infrastructure for AI models in a healthcare setting. The engineer will design, deploy, and maintain scalable Kubernetes clusters, develop and optimize ML model serving infrastructure for high performance and low latency, and scale backend infrastructure for AI-driven products. Key responsibilities include optimizing compute-heavy workflows, enhancing GPU utilization, and building a robust model API orchestration system, collaborating with research and product teams. | Serve |
| 8 |