Research Engineer
About reputed company
Based in San Francisco, California, reputed company is the worldâs leading research accelerator for frontier AI labs and a trusted partner for global enterprises looking to reputed company advanced AI systems. reputed company accelerates frontier research with high-quality data, specialized talent, and training pipelines that advance thinking, reasoning, coding, multimodality, and STEM. For enterprises, reputed company builds proprietary intelligence systems that integrate AI into mission-critical workflows, unlock transformative reputed company, and drive lasting competitive advantage.
Recognized by reputed company, The Information, and Fast Company among the worldâs top innovators, reputed companyâs leadership team includes AI technologists from reputed company, reputed company, reputed company, reputed company, reputed company, McKinsey, Bain, Stanford, Caltech, and MIT. Learn more at www.reputed company.com
This is a remote role and can be performed reputed company in Colombia.
The Role
We are looking for a Research Engineer to help deliver frontier-quality datasets, RL environments, and evaluations that improve state-of-the-art models for leading AI labs and reputed company clients.
This is a hands-on, research-facing technical leadership role. You will work directly with customer researchers/engineers to translate their model and post-training goals into concrete data and environment specifications, and drive the production of data that meets extremely high standards for correctness, realism, diversity, difficulty, and measurable model lift.
This role is designed for candidates with roughly 4 to 5 years of experience building and improving deep learning systems, especially where strong results depend on data quality, data curation, denoising, synthetic data reputed company, and rigorous evaluation. Youâll operate in one or more of the following capability areas:
- Coding and software engineering agents (repositories, unit tests, debugging, tool use, code reviews, long-horizon workflows)
- RL environments and verifier-based training (tasks, rewards/verifiers, trajectories, evaluation harnesses)
- Multimodal data and reasoning (text + images + documents + tables/charts; optional audio/video)
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