You will be cooperating with a leading provider of AI evaluation and optimization solutions, trusted by multinational companies to optimize AI agents and detect performance issues in large language models.
In this role, you will cooperate with a leading provider of AI evaluation and optimization solutions, directly contributing to a product that helps multinational enterprises optimize AI agents and detect LLM performance issues. You will be responsabile for designing and implementing complex Reinforcement Learning (RL) environments end-to-end, working at the intersection of research, systems engineering, and product. Collaborating with infrastructure and research teams, you will turn conceptual specifications into working environments with verifiable reward structures, automated verifiers, task generation pipelines, and reproducible simulations. These setups will span from API- and web-based tasks to multi-agent simulations, structured reasoning challenges, and knowledge-work environments used at scale by both researchers and customers.

Due to the client’s time zone, we would appreciate a candidate who can work until 10:00 p.m.

Steps in the recruitment process

1. HR call (max 10 min.)
2. Phone call with Technical Manager (max 10 min.)
3. Tech check with the Acai team (~ 30 min.)
4. Technical interview(s) with our client (30 - 60 min.)