AI Research Engineer: Agentic Post-Training

Alignerr Corp.; Neuquén; Remote; ARS 182,310,000 - 273,465,000; Full time

Job summary

Tether is hiring an AI Research Engineer (Agentic Post-training) to drive innovations in post-training methodologies. You will refine pre-trained models to deliver enhanced intelligence, learn to reason, plan, and autonomously invoke external tools for complex tasks on edge devices.

You will work on multimodal, scalable systems, from resource-efficient agents to multi-modal architectures optimized for tool-augmented decision making, with a strong emphasis on production-ready integrations.

Qualifications

• Degree in Computer Science, Machine Learning, or a related field; advanced degree (MS/PhD) preferred with a strong publication record in top-tier AI conferences.
• Experience with multimodal post-training workflows and data pipelines, particularly for agentic systems and tool use.
• Hands-on experience applying post-training at scale using distributed training frameworks (e.g., multi-node GPU environments).
• Demonstrated experience improving model capabilities in areas such as reasoning, tool use, and multi-agent coordination that achieve SOTA results.
• Proven track record of open-source contributions related to agentic systems or tool use (GitHub or Hugging Face).
• 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 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

Agentic post-training

Tool use

Reinforcement learning

Multi-turn reasoning

Data pipelines

Distributed training

Education

CS/ML degree

Tools

GitHub

Hugging Face

Job description

Tether is hiring an AI Research Engineer (Agentic Post-training) to drive innovations in post-training methodologies. You will refine pre-trained models to deliver enhanced intelligence, learn to reason, plan, and autonomously invoke external tools for complex tasks on edge devices.

You will work on multimodal, scalable systems, from resource-efficient agents to multi-modal architectures optimized for tool-augmented decision making, with a strong emphasis on production-ready integrations.