Together AI interview, decoded.

Together AI does not publish its interview process. The shape below comes from candidate reports collected by interview-prep sites, and every round is marked as reported. The sources agree on the coding rounds and the applied ML systems round; they differ on whether a take-home comes before the onsite. Reports put the whole loop at about two to four weeks.

The system design round is about the platform the company runs. Prep sites describe prompts rather than exact questions, so practise the shape: many models, shared GPUs, many customers, and a latency target.

• Serve 100+ open-source models on shared GPU capacity: Start from the traffic: which models are hot, their sizes and latency targets. Cover placement (which models share a GPU), autoscaling on queue depth, cold-start cost of loading weights, and routing. Name what you would measure first.
• A multi-tenant fine-tuning service with LoRA adapters: Keep one base model in memory and swap small adapters per request; discuss how many adapters fit, how to batch requests across adapters, and how to isolate customers' data.
• A KV cache for many concurrent chats: Size the cache per token and per request, then choose eviction and paging (as in paged attention), and say what happens to latency when memory runs out.

These prompts come from interview-prep sites, not from Together AI. Use them to practise the shape of the round.

The postings and the candidate reports point to the same few things.

• Working code over theory: the ML systems round asks you to write it, not describe it
• Performance judgement: explaining latency, throughput and memory trade-offs in what you built
• Hands-on inference experience with engines such as SGLang, vLLM or TensorRT-LLM, which the inference postings ask for
• Ownership of production systems, including on-call for a platform that runs around the clock
• Measured results in past projects, with what failed as well as what worked

No candidate account we could read lists exact questions, and prep sites describe prompts rather than verbatim problems. What follows is built from the rounds candidates describe, so what you practise matches what they score.

Together AI posts a US base range on its job ads, with equity and benefits on top (read 29 September 2026). The software engineer range covers junior to staff, so where you land depends on level. Its careers page lists salary and equity packages, 401(k) matching, meals and a relocation stipend for moves to the Bay Area. Calibrd benchmarks an offer against your level and location in the report.

1. Write attention, a batching loop and a streaming endpoint from scratch before the loop. Candidates report writing this kind of code, not only discussing it.
2. Be ready to explain every performance choice in numbers: latency, throughput and memory.
3. If you are applying for an inference role, know one engine well (SGLang, vLLM or TensorRT-LLM), including how it batches and caches.
4. Pick one or two production projects and prepare them in depth: scale, what you measured, what failed.
5. Practise medium algorithm problems against the clock: two in about 45 minutes is the pace reported.
6. Ask the recruiter whether your loop includes a take-home; reports disagree.

This guide covers Together AI's engineering and research hiring. For management and leadership roles the loop is similar but the bar shifts to people, delivery and strategy, so pair it with the leadership interview prep hub. The bar for your exact role comes from the role-by-role guides, and the prep that actually transfers is spoken, so run a mock interview before the real one.

Also interviewing at Crusoe, Harvey or Cursor? Their guides follow the same format, from the first screen to the offer.

• 01TechCrunch, Neocloud Together AI raises $800M, leaps to $8.3B valuationthe $800 million Series C at an $8.3 billion valuation led by Aramco Ventures, the earlier $305 million Series B at $3.3 billion, customers Cursor, Cognition and Decagon, annual bookings over $1.15 billion (1 July 2026)
• 02Together AI, jobs boardopen roles by department, mostly engineering, in San Francisco, Amsterdam, London, Bangalore, Pune and Singapore (read 29 September 2026)
• 03Together AI, Software Engineer, Inference / Compute Infrastructure Engineeringthe US base range of $160,000 to $280,000 plus equity and benefits, and the requirements: Go, Python or Rust, workflow orchestration, event-driven systems (read 29 September 2026)
• 04Together AI, Research Engineer, Post-Training Inferencethe US base range of $200,000 to $290,000, hands-on experience with SGLang, vLLM and TensorRT-LLM, and on-call for the platform (read 29 September 2026)
• 05Together AI, careersbenefits: salary and equity packages, 401(k) matching, meals, a relocation stipend for the Bay Area (read 29 September 2026)
• 06Design Gurus, What is the Together AI interview process like?candidate-reported rounds: recruiter call, two medium coding problems, the applied ML systems round (attention, streaming, batching), team interviews, two to four weeks
• 07techinterview.org, Together AI interview guidethe technical screen, a reported 4 to 8 hour take-home, onsite coding, inference system design prompts and CUDA tasks (24 April 2026, updated 3 July 2026)
• 08landedjobs, Together AI interview guidecompiled from public candidate reports: recruiter screen, coding, CUDA and systems, inference system design, hiring manager; reported problems including a FlashAttention forward step and a GPU-aware scheduler (July 2026)
• 09Extern, Together AI internship guideabout 350 employees, intern pay of $58 to $63 an hour, a PyTorch coding screen for research interns (September 2026)

Interview processes change. This reflects widely-reported and sourced conditions as of 2026 — confirm specifics with your recruiter, and treat it as a map rather than a guarantee.