Driving innovation in post-training methodologies, the full-time remote AI Research Engineer will refine pre-trained models to enhance intelligence and enable autonomous tool use for real-world applications across edge devices.
Key responsibilities
Conduct end-to-end research and engineering initiatives to advance post-training of agentic and tool-use models to achieve SOTA results
Design and enhance large-scale post-training systems, including data pipelines, training workflows, and evaluation frameworks
Collaborate with cross-functional teams to improve the usefulness and reliability of frontier models
Required qualifications
Degree in Computer Science, Machine Learning, or a related field; advanced degree (MS/PhD) preferred
Experience with multimodal post-training workflows and data pipelines for agentic systems
Hands-on experience applying post-training at scale using distributed training frameworks
Demonstrated experience improving model capabilities in reasoning, tool use, and multi-agent coordination
Proven track record of open-source contributions related to agentic systems or tool use
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