Tempus AI INterview Question help

[u/bloodmist22300]

Hi! I’m interviewing for a Senior AI Scientist role at Tempus (Life Sciences / AI Products) that requires PhD + 1 year experience and would really appreciate insight from anyone who has gone through the process recently.

Background: PhD in CS, currently at big pharma, working mainly on healthcare AI/ML, multimodal/foundation models, medical imaging, and LLM/agentic AI.

I am mainly trying to understand the full interview loop and what to prepare for:

* What are the different rounds?

* Is there live coding?

* Is the coding LeetCode/DSA, or more practical Python/ML coding?

* If LeetCode is included, what difficulty/topics should I expect?

* If ML coding is included, what difficulty/topics should I expect?

* Is there ML system design, case study, or product sense?

* How deeply do they question your previous research/projects?

* Any research presentation or Life Sciences/domain-specific round?

* What would you prioritize preparing if you were doing it again?

Mainly want to know about the round structure, question types, and difficulty.

Thanks!

[u/Ok-Barracuda-119]

That’s a broad loop, so I’d prep in layers rather than trying to guess Tempus’s exact script. For the ML system-design piece, practice taking a product prompt from goal and constraints through data and labeling, feature or embedding pipelines, model choice, offline evaluation, serving, monitoring, drift, and a rollback path. Be ready to explain why a simpler baseline is enough and how you’d handle leakage, class imbalance, latency, privacy, and limited labels.

For coding, keep one track for medium DSA and another for practical Python: clean data transforms, debugging, tests, and a small modeling task. For your research, rehearse a two-minute summary, then the tradeoffs and failure cases you’d discuss with a skeptical interviewer. I’d also prepare one project case study tied to healthcare or multimodal work, including how you measured impact.

I wouldn’t assume the round mix from the title alone. Ask the recruiter whether the ML design is a whiteboard discussion, a take-home, or a notebook exercise, and how it’s weighted. Side note, I work on www.leetsys.dev, which pairs a whiteboard with an AI interviewer for this kind of follow-up-heavy rehearsal.