AI research scientist

About the role

Lead an independent, high-impact research agenda on large language models and agentic systems, owning projects from early hypothesis through model training, evaluation, and production deployment.
Design and execute large-scale post-training experiments using supervised fine-tuning, reinforcement learning from human feedback (RLHF), RLAIF, DPO, and emerging alignment techniques — with a focus on improving multi-step reasoning, planning, and tool use in enterprise agentic workflows.
Develop novel evaluation benchmarks and methodologies that push beyond existing limitations, establishing rigorous measures for how well models perform on complex, real-world enterprise tasks.
Shape WRITER's model architecture and training roadmap by translating your research insights into concrete improvements to our enterprise-grade LLMs, working hand-in-hand with research engineering and product teams.
Publish and present original research at top-tier venues — NeurIPS, ICLR, ICML, ACL, and others — representing WRITER at the frontier of the field and contributing to the broader scientific community.
Mentor and uplevel fellow researchers and engineers on the team, helping set a high bar for scientific rigor, experimental design, and research culture.

What You'll Do

Lead an independent, high-impact research agenda on large language models and agentic systems, owning projects from early hypothesis through model training, evaluation, and production deployment.
Design and execute large-scale post-training experiments using supervised fine-tuning, reinforcement learning from human feedback (RLHF), RLAIF, DPO, and emerging alignment techniques — with a focus on improving multi-step reasoning, planning, and tool use in enterprise agentic workflows.
Develop novel evaluation benchmarks and methodologies that push beyond existing limitations, establishing rigorous measures for how well models perform on complex, real-world enterprise tasks.
Shape WRITER's model architecture and training roadmap by translating your research insights into concrete improvements to our enterprise-grade LLMs, working hand-in-hand with research engineering and product teams.
Publish and present original research at top-tier venues — NeurIPS, ICLR, ICML, ACL, and others — representing WRITER at the frontier of the field and contributing to the broader scientific community.
Mentor and uplevel fellow researchers and engineers on the team, helping set a high bar for scientific rigor, experimental design, and research culture.

What You Need

• 7+ years of hands-on ML research experience, with deep expertise in large language model pre-training and post-training — you've trained models at scale, debugged distributed jobs, and shipped improvements that made a measurable difference.
• A Ph.D. in Computer Science, Machine Learning, NLP, or a related field — or equivalent demonstrated research experience with a strong portfolio of independent, published work.
• Expert-level knowledge of post-training methods including SFT, RLHF, RLAIF, DPO, GRPO, and related alignment and reasoning techniques, with a track record of applying them to real, production-grade systems.
• Strong command of Python and PyTorch (or JAX), with the engineering depth to build and scale training pipelines, evaluation infrastructure, and data synthesis workflows yourself — not just direct others to do it.
• A meaningful publication record at competitive ML/AI venues (NeurIPS, ICLR, ICML, ACL, EMNLP, or equivalent), evidencing your ability to originate ideas and execute on a multi-month research agenda independently.
• Hands-on experience designing or evaluating agentic systems — models that plan, reason through multi-step tasks, use tools, and recover gracefully from errors — with a nuanced understanding of where they break and how to fix them.
• The instincts and orientation that match WRITER's values: you Connect — you collaborate openly across research, engineering, and product and communicate complex ideas with clarity to both technical and non-technical audiences; you Challenge — you ask the hard questions, push back on conventional wisdom, and pursue the research directions others haven't tried yet; you Own — you drive your projects end-to-end with urgency, take accountability for results, and care deeply about the impact your work has on real customers.