AI research scientist
Remote • San Francisco, CA • FullTime
Posted 11h ago
Job Location
San Francisco, CA
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Research Engineer
About the job
AI research at WRITER focuses on building the scientific foundation for enterprise AI deployments. As an AI Research Scientist, you will drive a high-impact research agenda centered on large language models, agentic reasoning, and system-level capabilities essential for enterprise-scale AI. This role offers a unique opportunity to advance the field while directly contributing to products used by hundreds of thousands daily. You will work on post-training, planning, multi-step reasoning, and agentic workflows, directly shaping the next generation of enterprise AI performance and scalability. The role is hybrid, based in San Francisco or New York City, reporting to the VP of AI research. We are open to hiring at Senior, Staff, and Sr. Staff levels.
Responsibilities
- Lead an independent research agenda on large language models and agentic systems, managing projects from hypothesis to production deployment.
- Design and execute large-scale post-training experiments using techniques like SFT, RLHF, RLAIF, and DPO to enhance multi-step reasoning, planning, and tool use in enterprise agentic workflows.
- Build novel evaluation benchmarks and methodologies to rigorously measure model performance on complex enterprise tasks.
- Develop scalable data synthesis and curation pipelines, including LLM-as-judge frameworks and adversarial dataset construction, to drive model improvement.
- Translate research insights into concrete improvements for enterprise-grade LLMs, collaborating with research engineering and product teams.
- Publish and present original research at top-tier AI/ML venues.
- Mentor researchers and engineers, promoting scientific rigor and a strong research culture.
Requirements
- 7+ years of hands-on ML research experience, with deep expertise in large language model pre-training and post-training.
- Ph.D. in Computer Science, Machine Learning, NLP, or a related field, or equivalent demonstrated research experience with a strong publication record.
- 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 production 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).
- Hands-on experience designing or evaluating agentic systems, including planning, multi-step reasoning, tool use, and error recovery.
- Demonstrated alignment with WRITER's values: Connect, Challenge, and Own.
Benefits
- Generous PTO
- Company holidays
- Medical, dental, and vision insurance