Member of Technical Staff - ML Research
Architect Labs· Machine Learning
Palo AltoFull-timePosted 3mo ago
About the role
Frontier AI lab focusing on custom silicon; responsible for RL research and production-ready ML pipelines for chip design, verification, and exploration tasks.
Responsibilities
- Co-designing and implementing the Reinforcement Learning environments and algorithms, Reward Models trainings and reward signal experiments.
- Work at the intersection of cutting-edge research and production engineering for chip designs, implementing, scaling, and improving post-training techniques to enhance model capabilities and usability.
- Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation, ensuring that theoretical performance translates into production-ready implementations.
- Own the end-to-end RL workflow—from reward modeling and environment design to test-time optimization and scaling.
- Collaborate with research teams to translate emerging techniques into production-ready implementations and debug complex issues in training pipelines and model behavior.
Qualifications
- PhD in Computer Science, Computer Engineering, EECS, Mathematics, or a closely related field with specialization in ML/AI (or BS/MS with strong research engineering background).
- Deep expertise in reinforcement learning and post-training, with a proven track record of taking models from research to real-world deployment.
- Strong industry or research background building end-to-end ML pipelines. Experience RL and fine-tuning LLMs and code models for reasoning, tool use, and structured coding tasks.
- Strong software engineering skills with experience building complex ML systems. Comfortable with large-scale distributed systems, high-performance computing, and distributed training frameworks (e.g., PyTorch, CUDA, QLoRA, ZeRO).
- Adept at analyzing and debugging model training processes. Capable of balancing research exploration with engineering rigor and operational reliability.
- Fast-moving builder who can prototype, benchmark, and productionize training pipelines with tight feedback loops.
Skills
Required:Reinforcement LearningPost-Training MLEnd-to-end ML PipelinesDistributed Systems
Nice to have:LLM / Code Model Fine-tuning
Benefits
- Competitive salary and meaningful equity stake
- Fast-paced startup with autonomy and visible impact
- Cutting-edge AI-driven chip design challenges
Last updated Sep 20, 2026. Interested? Apply on the company site.
About Architect Labs
Architect Labs
Architect is a frontier AI lab for chip design.
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