Tether Data is seeking an AI Research Engineer to develop post-training methods for large language models, focusing on agentic reinforcement learning, tool use, memory, multi-agent systems, and human feedback. The role is fully remote and involves building reliable, efficient AI agents for developer and consumer products.
Overview
Compensation not specified
remote
full-time
No experience required (senior level)
Technologies
- PythonPyTorchJAXDistributed TrainingSFTRLHFDPOReinforcement LearningLarge Language ModelsAgentic AIEvaluation FrameworksData Pipelines
Responsibilities
- Design, implement, and evaluate post-training recipes for large language models, including SFT, RLHF, DPO, and agentic reinforcement learning.
- Build evaluation harnesses and benchmarks for agentic capabilities such as tool use, planning, memory, and multi-step reasoning.
- Develop data pipelines for collecting, cleaning, and curating high-quality training and evaluation data from real-world interactions.
- Run experiments at scale, analyze results, and iterate on model behavior, prompts, and training configurations.
- Collaborate with product and engineering teams to integrate research prototypes into production systems.
- Stay current with research in LLMs, agentic AI, and reinforcement learning, and share findings with the team.
- Contribute to internal tools and infrastructure for model training, evaluation, and deployment.
- Publish research findings and represent Tether Data at conferences and in the open-source community where appropriate.
Qualifications
- Strong background in machine learning, with hands-on experience training and fine-tuning large language models.
- Deep understanding of post-training methods, including SFT, RLHF, DPO, and reinforcement learning.
- Experience building evaluation frameworks and benchmarks for LLM capabilities.
- Proficiency in Python and modern ML frameworks such as PyTorch, JAX, or similar.
- Experience with distributed training and large-scale experimentation.
- Familiarity with agentic systems, tool use, and multi-agent architectures.
- Strong problem-solving skills and ability to work independently in a remote, async environment.
- Working proficiency in English is required.
Benefits
- Competitive salary and benefits package; exact compensation not specified.
- 100% remote work — work from anywhere in the world.
- Flexible working hours and a strong focus on work-life balance.
- Opportunity to work on cutting-edge AI research with a global team.
- Access to state-of-the-art compute infrastructure.
- Professional development opportunities, including conferences and training.
- Collaborative, transparent, and mission-driven work environment.