Tempus AI
Vertical AI · Precision medicine AI (NASDAQ:TEM)
- HQ
- Chicago, US
- Founded
- 2015
- Funding
- Public (TEM)
- Website
- tempus.com
Vertical AI · Precision medicine AI (NASDAQ:TEM)
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).
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 |
|---|---|---|
| Translational Scientist, Applied Machine Learning and Agentic AI, Pharma R&D This role focuses on building cutting-edge agentic frameworks for automating the discovery of prognostic and predictive models in oncology, integrating LLM orchestration with computational biology. The scientist will develop 'deep agents' for hypothesis generation, experimental design, and multimodal ML modeling using foundation models, leveraging Tempus' extensive multimodal patient datasets. | Agent | 8 |
| Staff/Senior Machine Learning Engineer, Clinical AI Staff/Senior Machine Learning Engineer to build and operate production AI pipelines, including LLM-powered extraction, batch orchestration, and inference, with a focus on reliability, cost, and latency. The role involves designing and maintaining orchestration, building observability and eval infrastructure, shipping platform tooling, and collaborating with ML Scientists and platform teams. Experience with Python, microservices, cloud-native services, ML frameworks (LangGraph, PyTorch, spaCy), and design documentation is required. Preferred qualifications include experience with on-call rotations, incident response, building eval systems, production LLM application experience, internal platforms/SDKs, and clinical/biomedical data. | AgentEval Gate | 8 |
| 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 |
| Sr. Data Scientist, Translational Research This role focuses on building specialized AI agents and workflows that leverage LLMs to help clients derive insights from large-scale biomedical data. It involves client onboarding, scientific problem-solving, platform guidance, and creating AI-assisted tools for data analysis. The role requires experience in data science, machine learning, Python/R, and putting data science workflows into production, with a strong emphasis on using AI-assisted development tools. | Agent | 7 |
| Customer Success AI Strategy & Agent Development Lead Lead the end-to-end development of AI agents within the Customer Success organization, focusing on identifying commercial opportunities, hands-on prompt engineering, and stakeholder alignment. This role bridges technical build teams and customer success to solve capacity and physician needs. | Agent | 7 |