About this role
Developers who enjoy turning complex theoretical concepts into production models that serve hundreds of thousands of users will find a natural home in this role. The research team builds the scientific foundation for enterprise generative AI, focusing on large language models, agentic workflows, and system-level capabilities. Responsibilities include driving a research agenda from hypothesis through model training, designing post-training experiments, and shaping the architecture of enterprise-grade LLMs.
The position exists because enterprises are shifting from experimentation to deep operational integration, requiring advanced research that ships directly into products. Candidates who succeed here possess deep technical expertise in machine learning, a strong publication record, and the engineering capability to build scalable training pipelines independently.
What you will do
- Lead an independent research agenda focused on large language models and agentic systems, managing projects from hypothesis to production deployment.
- Design and execute large-scale post-training experiments using supervised fine-tuning, reinforcement learning from human feedback, and emerging alignment techniques.
- Build novel evaluation benchmarks and methodologies to measure model performance on complex enterprise tasks.
- Develop scalable data synthesis and curation pipelines, including LLM-as-judge frameworks and synthetic data generation.
- Shape model architecture and training roadmaps by translating research insights into concrete product improvements.
- Publish and present original research at top-tier venues such as NeurIPS, ICLR, ICML, and ACL.
- Mentor fellow researchers and engineers while setting high standards for scientific rigor and experimental design.
What you need
- Bring at least 7 years of hands-on machine learning research experience with deep expertise in large language model pre-training and post-training.
- Hold a Ph.D. in Computer Science, Machine Learning, NLP, or a related field, or possess equivalent demonstrated research experience with a published portfolio.
- Demonstrate expert-level knowledge of post-training methods such as SFT, RLHF, RLAIF, DPO, and GRPO.
- Maintain a strong command of Python and PyTorch or JAX to build and scale training pipelines and evaluation infrastructure.
- Provide a meaningful publication record at competitive venues like NeurIPS, ICLR, ICML, ACL, or EMNLP.
- Possess hands-on experience designing or evaluating agentic systems that plan, reason through multi-step tasks, and use tools.
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
- Health savings account for eligible plans with company contribution
- Competitive compensation, company stock options and 401k
Skills and tech stack
Questions candidates ask
What is the remote work policy for this role?
This role is hybrid, based out of the San Francisco or New York City hub.
What is the compensation range for this position?
Compensation ranges from $199K to $325K alongside offers for equity, scaled to match your experience, expertise, and the scope of the role.
What seniority levels are being considered for this opening?
The role is open to Senior, Staff, and Sr. Staff applicants.
Who does this position report to?
You will report directly to the VP of AI research.