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Writer is an enterprise generative AI platform used by leading companies like Mars, Marriott, Uber, and Vanguard to build and deploy AI agents grounded in their data. The company is valued at $1.9B and backed by top-tier investors including Premji Invest, Radical Ventures, and ICONIQ Growth.
As an AI Research Scientist, you will drive a high-impact research agenda focused on large language models, agentic reasoning, and system-level capabilities that enable AI to work effectively at enterprise scale. This role sits at the intersection of advancing the field and shipping research directly into products used by hundreds of thousands of people daily.
You will lead independent research projects from hypothesis through model training, evaluation, and production deployment. Key responsibilities include designing and executing large-scale post-training experiments using supervised fine-tuning, RLHF, RLAIF, DPO, and emerging alignment techniques with a focus on multi-step reasoning, planning, and tool use in enterprise workflows. You will build novel evaluation benchmarks and methodologies that measure model performance on complex, real-world enterprise tasks. You will develop scalable data synthesis and curation pipelines including LLM-as-judge frameworks and synthetic data generation. You will shape Writer's model architecture and training roadmap by translating research insights into concrete improvements to enterprise-grade LLMs, working closely with research engineering and product teams. You will publish and present original research at top-tier venues (NeurIPS, ICLR, ICML, ACL, etc.) and mentor fellow researchers and engineers on the team.
The role is hybrid, based out of San Francisco or New York City, and reports to the VP of AI Research. Writer is open to hiring at Senior, Staff, and Sr. Staff levels with compensation scaled to experience and scope.
REQUIREMENTS:
- 7+ years of hands-on ML research experience with deep expertise in large language model pre-training and post-training; demonstrated experience training models at scale, debugging distributed jobs, and shipping improvements
- Ph.D. in Computer Science, Machine Learning, NLP, or 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 track record of applying them to production-grade systems
- Strong command of Python and PyTorch (or JAX) with engineering depth to build and scale training pipelines, evaluation infrastructure, and data synthesis workflows
- Meaningful publication record at competitive ML/AI venues (NeurIPS, ICLR, ICML, ACL, EMNLP, or equivalent) demonstrating ability to originate ideas and execute multi-month research agendas independently
- Hands-on experience designing or evaluating agentic systems—models that plan, reason through multi-step tasks, use tools, and recover from errors—with nuanced understanding of failure modes and solutions
- Alignment with Writer's values: collaboration across research, engineering, and product with clear communication to technical and non-technical audiences; willingness to challenge conventional wisdom and pursue novel research directions; drive to own projects end-to-end with urgency and accountability for customer impact
About Writer
AI / Data / Infrastructure; SaaS / Enterprise Software — enterprise generative AI platform for business teams.
