Fall 2026
Member of Technical Staff Research Intern
Posted on 7/21/2026
Architect Labs
No salary listed
Palo Alto, CA, USA
In Person
On-site in Palo Alto, CA. Local residency preferred.
Category
 Software Engineering (1) |
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Required Skills
Python
Pytorch
Reinforcement Learning
Requirements
- Education: Currently pursuing a PhD or Master’s degree in Computer Science, Machine Learning, Mathematics, or a related field. Exceptional undergraduates with strong research experience are also encouraged to apply.
- RL Knowledge: Strong academic understanding or project experience with Reinforcement Learning (e.g., PPO, DPO, GRPO). You should be comfortable reading and implementing concepts from recent research papers.
- Coding Proficiency: Strong proficiency in Python and deep learning frameworks (PyTorch). You should be able to write clean, efficient research code.
- Research Mindset: A fast learner who is comfortable navigating ambiguity. You enjoy analyzing complex problems and iterating quickly on experiments.
- LLM Familiarity: Experience with training or fine-tuning Large Language Models (LLMs) or familiarity with the modern NLP stack (Transformers, HuggingFace, etc.)
Responsibilities
- Responsible for co-designing and implementing the Reinforcement Learning experiments (GRPO/PPO/DPO), training data mixes and reward signal explorations.
- Contribute to research on post-training techniques, running ablation studies to improve model reasoning and alignment capabilities.
- Implement and test new algorithms for model fine-tuning and evaluation, helping to translate research papers into working prototypes.
- Analyze experimental results and debug model behavior to help establish best practices for our training recipes.
Desired Qualifications
- Previous internship experience at frontier AI labs or research organizations.
- Publications (or submissions) in top ML venues (NeurIPS, ICLR, ICML) or EDA venues (DAC, ICCAD).
- Familiarity with hardware design concepts (Verilog, RTL, EDA tools), though not required.