Tempus AI
Vertical AI · Precision medicine AI (NASDAQ:TEM)
- HQ
- Chicago, US
- Founded
- 2015
- Funding
- Public (TEM)
- Website
- tempus.com
Tempus AI currently has 12 active AI-related job listings. The majority of these roles, 75%, are focused on agents, with data and post-training roles making up the remainder. Engineering is the most frequent function for these positions, with hiring concentrated in the United States. The company is frequently seeking candidates with experience in agent orchestration, LLM observability, and fine-tuning. Over the last 30 days, Tempus AI has added 8 new AI roles, representing a 100% increase compared to the previous 30-day period.
Currently tracking 8 active AI roles, down 45% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $73k–$260k (avg $175k).
Vertical AI · Precision medicine AI (NASDAQ:TEM)
Tempus AI currently has 17 active AI-related roles in our index. The most common open titles are: Associate Director RWE, PharmaR&D, Customer Success AI Strategy & Agent Development Lead, Data Scientist II, Real World Evidence (RWE), Pharma R&D, Detection Engineer, Director, Epidemiology & Methodological Innovation. Most positions are in Engineering and Research.
Tempus AI's active AI hiring is concentrated in: agents (65%), data (29%), post-training (6%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Tempus AI is hiring AI talent in: United States (15 roles), Spain (1 role).
Job postings at Tempus AI most frequently reference: agent orchestration, llm observability, fine tuning, tool use, rag.
In the past 30 days, Tempus AI has posted 5 new AI-related roles. That is a -44% change versus the prior 30 days (9 → 5).
| Title | Stage | AI score |
|---|---|---|
| Staff AI Scientist - AI Products / Life Sciences Staff AI Scientist role focused on researching, designing, and deploying multimodal AI models for precision medicine and therapeutic solutions in healthcare, leveraging large clinical and molecular datasets. The role involves technical leadership, algorithmic innovation, collaboration with life sciences companies, ensuring regulatory alignment, and scientific contribution through publications. Requires a Ph.D., 5+ years of industry experience in end-to-end ML model development, and expertise in deep learning, computer vision, and multimodal modeling. | Post-trainServe | 8 |