Together AI
Data AI · Open-source model infra
- HQ
- San Francisco, US
- Website
- together.ai
Together AI currently has 22 active AI-related job listings. The majority of these roles, 95%, are focused on serving infrastructure, with one role in post-training. The company is primarily hiring for Engineering positions, with 20 roles available, and is seeking candidates in the United States and the Netherlands. Frequent technical tags include model serving, inference infrastructure, and fine-tuning, suggesting a focus on deployment and optimization of AI models. In the last 30 days, Together AI added 5 new AI roles, a 150% increase from the previous 30-day period.
Currently tracking 20 active AI roles, down 14% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $160k–$300k (avg $226k).
Data AI · Open-source model infra
Together AI currently has 28 active AI-related roles in our index. The most common open titles are: Solutions Architect (2), AI Infrastructure Engineer, AI Researcher, Core ML (Turbo), Backend Software Engineer — Data Platform & AI Data Products, Customer Support Engineer (Inference). Most positions are in Engineering and Research.
Together AI's active AI hiring is concentrated in: serving infrastructure (89%), post-training (7%), agents (4%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Together AI is hiring AI talent in: United States (23 roles), Netherlands (3 roles), United Kingdom (1 role).
Job postings at Together AI most frequently reference: model serving, inference infra, fine tuning, llm observability, rl post training.
In the past 30 days, Together AI has posted 9 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Frontier Agents Intern (Fall 2026) Research intern focused on building, aligning, and scaling frontier AI agent systems for complex multi-step tasks across text and speech. Projects involve developing new training methods, curating datasets, studying failure modes, and building scalable infrastructure for agent operations. | AgentPost-train | 9 |