Remote AI Research Engineer: Agentic Models & Tooling

Visa Hunt; United States; Remote; USD 120,000 - 190,000; Full time

Job summary

Tether is seeking a leader in AI who can advance post-training for agentic, tool-augmented systems across edge devices. You will refine models to reason, plan, and autonomously invoke tools to solve real-world tasks.

You'll work across multi-modal architectures, optimize for efficiency, and push SOTA through data pipelines, evaluation suites, and cross-functional collaboration with research and engineering teams.

Qualifications

• Degree in Computer Science or Machine Learning; MS/PhD preferred.
• Experience with multimodal post-training workflows and data pipelines.
• 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.
• Publications at leading AI conferences (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, ECCV).

Responsibilities

• Conduct end-to-end research and engineering initiatives to advance post-training of agentic and tool-use models to achieve SOTA results.
• Drive broad, cross-cutting model improvements, including factuality, instruction adherence, tool/function use, multi-agent coordination, and reasoning calibration.
• Design and enhance large-scale post-training systems, including data pipelines, training workflows, evaluation frameworks, and benchmark infrastructure.
• Develop rigorous evaluation suites and diagnostic tools to assess model readiness for deployment.
• Strengthen feedback loops from real-world product usage, incorporating both explicit and implicit user signals into post-training.
• Collaborate with tooling, product, and training teams to improve the usefulness, reliability, and agentic capabilities of frontier models.
• Closely liaise with research, engineering and cross-functional teams to determine which integrations are production-ready for inclusion in major model releases.

Skills

Multimodal ML

Agentic systems

Tool use

Distributed training

Open-source contributions

Publications in AI conferences

Education

MS/PhD preferred

Tools

GitHub

Hugging Face

Job description

Tether is seeking a leader in AI who can advance post-training for agentic, tool-augmented systems across edge devices. You will refine models to reason, plan, and autonomously invoke tools to solve real-world tasks.

You'll work across multi-modal architectures, optimize for efficiency, and push SOTA through data pipelines, evaluation suites, and cross-functional collaboration with research and engineering teams.