AI Research Engineer (Agentic Post-training) - 100% Remote Worldwide
Tether Operations Limited
WorldwideremotePosted 16 days ago
Skill Required
AI-Research-and-EngineeringLLM-Post-TrainingAgentic-AI-DevelopmentMachine-Learning-ResearchTool-Use-DevelopmentAI-Research-EngineerAI-ML-Research-EngineerRemote-Senior-AI-EngineerML-AI-Research-EngineerResearch-EngineerAI EngineerAIMachine Learningrelated fieldLangChainEngineeringBlockchainData StructuresbuildingfintechTestNGdesignGitRustNode.jsandFulltime
Key highlights
- No specific salary figure stated in the source
- Requires advanced degree (MS/PhD) preferred with strong publication record in top-tier AI conferences
- Publications at leading AI conferences required (NeurIPS, ICML, ICLR, ACL, CVPR, ECCV)
- Hands-on experience with multimodal post-training workflows at scale using distributed training frameworks required
- Open-source contributions related to agentic systems or tool use required
- Role focuses on pushing SOTA (State of the Art) results in agentic AI with autonomous tool invocation on edge devices
Role overview
At Tether, we're pioneering a global financial revolution by building cutting-edge blockchain solutions that empower businesses to seamlessly integrate reserve-backed tokens across blockchains. Our innovative product suite includes the world's most trusted stablecoin, USDT, alongside pioneering digital asset tokenization services, sustainable energy solutions for Bitcoin mining, data infrastructure for AI and peer-to-peer technology, education platforms for the digital economy, and emerging technologies at the intersection of technology and human potential. As a member of the AI model team, you will drive innovation in post-training methodologies with a special focus on agentic behaviors and tool use, refining pre-trained models to deliver enhanced intelligence, domain-specific capabilities, and autonomous tool invocation for real-world multi-step tasks on edge devices.
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
- Curate agentic training data (e.g., trajectories of tool use, reasoning chains, environment interactions)
- Strengthen baseline performance
- Identify as well as resolve bottlenecks in post-training for tool augmented agents to achieve SOTA model quality
Requirements
- 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)
Additional details
- The role focuses on post-training methodologies with special focus on agentic behaviors and tool use
- Models will run on edge devices (i.e., smartphones)
- Work spans from streamlined, resource efficient agents that run on limited hardware to complex multi modal architectures integrating text, images, and audio
- All optimized for tool augmented decision making
- The goal is to build models that not just know but also act, use tools, and adapt
- Tether is a global, remote-first company with a lean, fast-moving team
- Excellent English communication skills required
- The team works on innovations ranging from Tether Finance (USDT stablecoin) to Tether Power (sustainable Bitcoin mining energy solutions), Tether Data (AI and peer-to-peer infrastructure), Tether Education (digital learning platforms), and Tether Evolution (emerging technologies)
- Original posting source: Himalayas