Adam, AdamW and decoupled weight decayML designWrite Adam's update: the first and second moment estimates, bias correction and the step. Why is adding an L2 penalty to the loss not the same as weight decay once Adam's…
Last asked Sep 2026
Mistral AI LLM knowledge screen interview
Round 2 of 5 · 8 questions reported
- Length
- 60 min
- Format
- Structured technical check with a Mistral engineer
- They grade
- Precise answers on model internals: KV caching, tokenization, context windows, embedding retrieval
- Heads-up
- Reported by one guide as a gate before coding; the other describes a classic coding phone screen here. Ask which you will get. A 2026 research-engineering screen was direct questions, no coding: tensor versus pipeline parallelism, mixture of experts, RMSNorm, diffusion, Adam and AdamW, DPO versus RLHF, and keeping GPUs fed with data.
Questions Mistral AI asks in this round 8
- Keep GPUs fed: fix a training job that waits on its dataML designA training job's GPUs sit idle a third of the time waiting for the next batch. How do you prove the input pipeline is the bottleneck, and then fix it? Cover profiling, parallel…Last asked Sep 2026
- Mixture of experts and expert parallelismML designExplain how a mixture-of-experts transformer layer works and follow a batch of tokens through it: the router, top-k selection, the all-to-all exchange that sends tokens to experts…Last asked Sep 2026
- Reward-model RLHF versus direct preference optimizationML designWalk through a classic RLHF pipeline: supervised fine-tuning, a reward model trained on preference pairs, then policy optimization (PPO) with a KL penalty to the reference model…Last asked Sep 2026
- RMSNorm versus LayerNorm in a transformer blockML designWrite the formulas for LayerNorm and RMSNorm and say what each normalizes. What does RMSNorm give up by skipping the mean, why does it work about as well in practice, and why do…Last asked Sep 2026
- Tensor parallelism versus pipeline parallelismML designA transformer is too big for one accelerator. Explain how tensor parallelism and pipeline parallelism each split it: what is cut, what crosses the wire and when, where the idle…Last asked Sep 2026
- The forward and reverse processes of a diffusion modelML designExplain how a diffusion model is trained and how it generates. Describe the forward process that adds noise step by step, the reverse process the network learns, the usual…Last asked Sep 2026
- Greedy, top-k and top-p decoding for a language modelCodingYou get a toy language model with a small vocabulary whose forward pass returns next-token logits for the tokens so far. Using NumPy, write the generation loop and three ways to…Last asked Jul 2026