Provides infrastructure/tools to train, fine-tune, and run frontier models; actively listing many roles.
Questions will use Technical Screen and System Design signals from Together AI.
Difficulty
4.2/5 — Hard
Timeline
3 to 6 weeks
Formats
Recruiter Screen
Initial conversation to discuss background, interest in AI infrastructure, and alignment with the company mission.
Technical Screen
Stay updated on the latest research papers and open-source models released by the community.
Demonstrate a strong understanding of the AI infrastructure stack, including PyTorch and CUDA.
Be prepared to discuss why you want to work on infrastructure rather than just model application.
A deep dive into technical skills, often involving coding or system design relevant to GPU infrastructure or machine learning engineering.
On-Site / Final Round
A series of interviews with team members and leadership covering technical depth, system design, and cultural fit.
Use the STAR method to highlight your problem-solving process.
How do you approach designing a distributed training pipeline for a multi-billion parameter model?
PracticeDiscuss data parallelism, model parallelism, and communication overhead.