AI Research Engineer – Agentic Post-training

Tether.to

. Conduct end-to-end research and engineering initiatives to advance post-training of agentic and tool-use models to achieve SOTA results.

Posted 5/19/2026full-timeRemote • 🌎 Anywhere in the WorldMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

Node.js

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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 (code, datasets, or models) on platforms such as GitHub or Hugging Face.
Publications at leading AI conferences (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, ECCV).

Benefits

Comp & perks

Flexible work arrangements
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningdata pipelinestraining workflowsevaluation frameworksbenchmark infrastructuredistributed training frameworksmulti-node GPU environmentsmodel evaluationpost-trainingagentic systems

Soft Skills

collaborationcross-functional teamworkcommunicationfeedback incorporationproblem-solvinganalytical thinkingadaptabilityinitiativeattention to detailcreativity

Certifications

degree in Computer Sciencedegree in Machine Learningadvanced degree (MS/PhD)publication record in AI conferences