🛠 Tech Stack

💼 About This Role

As a Student Researcher, you'll work at the intersection of LLM post-training, evaluation, and data efficiency, owning a scoped research project mentored by a senior scientist. Your work can ship directly into our production stack and become a publishable research contribution. You'll tackle novel RLHF pipelines, new benchmarks, or synthetic data generation strategies.

🎯 What You'll Do

• Design and run experiments on **LLM post-training** pipelines using RLHF or GRPO.
• Develop new **multilingual or domain-specific benchmarks** for LLM evaluation.
• Implement **active-learning loops** or data value estimation techniques.
• Write and submit manuscripts to top-tier ML conferences.

📋 Requirements

• Current PhD student in CS, ML, NLP, or related field.
• Publication record at NeurIPS, ICML, ACL, EMNLP, or ICLR.
• Hands-on experience with PyTorch, JAX, or DeepSpeed for LLM training.
• Strong empirical rigor and experience with distributed training.

✨ Nice to Have

• Prior work on RLHF, evaluation tooling, or data selection.
• Contributions to open-source LLM frameworks.
• Experience with teaching or public speaking for reading groups.

🎁 Benefits & Perks

• 💰 Competitive monthly stipend of $7K–$13K based on hours.
• 🧑‍🔬 Mentorship from senior scientists with publishing goals.
• 🌍 Work on globally impactful AI used by Fortune 500 and top labs.
• 🏢 Onsite in San Francisco with collaborative research environment.
• 📄 Archive-ready manuscript or conference submission at top venues.

🚩 Heads Up

• Role requires PhD student status and publication record, yet title implies junior 'Student Researcher' position.
• Vague compensation range based on hours (20-40 hrs/week), possibly indicating unclear workload expectations.