Sobre esta vaga de AI Enterprise Engineer na Bespoke Labs
About Bespoke Labs
Bespoke Labs is an applied AI research lab pioneering data and RL environment curation for training and evaluating agents.
Recently, we curated Open Thoughts, one of the best open reasoning datasets used by multiple frontier labs, trained SOTA specialized models such as Bespoke-MiniChart-7B and Bespoke-MiniCheck, and taught agents to do multi-turn tool-calling with reinforcement learning.
We are also core contributors to Terminal-bench, a leading benchmark for agents used by most frontier labs. Bespoke Labs creates RL environments for frontier labs and specialized agents for enterprises.
About The Role
We are looking for AI Enterprise Engineers who are able to work directly with our Enterprise customers, owning strategy and execution. Your work will involve defining model and agent specifications, understanding user pain points and designing specialized agents.
You will benchmark models and create datasets for customer needs using Bespoke Labs tools. Further, the role requires improving model performance by context optimization, and post-training techniques like SFT and RL. Bespoke Labs contributes to core research in this space (e.g. see the latest prompt optimization techniques like GEPA). You will be able to learn and innovate on advanced recent AI techniques.
AI engineers combine research intuition with practical execution. You will need to understand agent behavior, identify reward hacking and analyze failure modes. Then, you will translate that understanding into enterprise deployed specialized agents.
The Ideal candidate meets at least the following requirements
Experience in Python and ML product development.
Strong CS or ECE Background, MS/PhD degree preferred.
Demonstrated experience of ML and AI fundamentals, including model evaluation, training and fine-tuning.
Experience on deploying models in production.
Research is in our DNA
Bespoke Labs is committed to research and publication. The ideal candidate is interested in research and publication. Experience and publications in Top AI venues (NeurIPS, ICML, ICLR) is a plus and continuing research curiosity is desired.
