Staff AI Research Scientist

Role Overview

• 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
• Build novel evaluation benchmarks and methodologies that push beyond existing limitations, establishing rigorous measures for how well models perform on complex, real-world enterprise tasks
• Develop scalable data synthesis and curation pipelines that generate the high-quality training signal driving model improvement — including LLM-as-judge frameworks, synthetic data generation, and adversarial dataset construction
• 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

Requirements

• 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
• 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
• 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
• 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

Tech Stack

• Python
• PyTorch

Benefits

• Generous PTO, plus company holidays
• Medical, dental, and vision coverage for you and your family
• Paid parental leave for all parents (16 weeks)
• Fertility and family planning support
• Early-detection cancer testing through Galleri
• Flexible spending account and dependent FSA options
• Health savings account for eligible plans with company contribution
• Annual work-life stipends for:
• Wellness stipend for gym, massage/chiropractor, personal training, etc.
• Learning and development stipend
• Company-wide off-sites and team off-sites
• Competitive compensation, company stock options and 401k