Together AI
Cloud for fast inference, fine-tuning and training of open models
Interview in a few hours? A quick sprint for Together AI
AI in interviews
No public policy found. Assume no AI assistance in live rounds unless your recruiter says otherwise.
Typical interview loop
How Together AI usually runs it for applied AI and LLM engineer roles.
- Focus: Motivation, logistics
Recruiter call
A roughly 30-minute video call on your background, why Together AI, and which rounds your loop will include.
- Focus: Coding, ML-systems instincts
Technical phone screen
An hour of live coding on one medium-to-hard problem that often carries an ML-systems twist such as streaming or request batching.
- Focus: DSA speed and clarity
Algorithmic coding
Timed data-structure problems, sometimes framed around infrastructure like scheduling work across GPUs, where pace is the main challenge.
- Focus: Inference internals
Applied ML-systems coding
Implement a piece of an inference engine (for example an attention or KV-cache component) and explain its performance trade-offs.
- Focus: AI infra design
System design
Design AI infrastructure at scale, such as multi-tenant model serving or a fine-tuning service, reasoning about GPU memory, batching and tail latency.
- Focus: Past projects, mission fit
Team and leadership conversations
Project deep dives with engineers from several teams, then a closing chat with a senior leader on motivation and fit.
How it weights your plan
Selecting Together AI when you build a plan multiplies each topic’s priority score:
Official prep and resources
Public candidate write-ups
Ready to prepare for Together AI?
Get a day-by-day plan that leans toward what Together AI tests most.
Build my Together AI prep planCompany names and logos are trademarks of their owners, shown only to identify them. SEEKHO isn’t affiliated with or endorsed by any of these companies.