Member of Technical Staff - ML Research

About the Company

Architect is a frontier AI lab for chip design. We build AI models and tools for on-demand custom ASICs at scale, co-designing custom ASICs alongside evolving ML workloads to unlock new hardware capabilities.

Responsibilities

• Co-design and implement Reinforcement Learning environments, algorithms, and Reward Model trainings
• Implement, scale, and improve post-training techniques to enhance model capabilities
• Design and run robust pipelines for model fine-tuning and evaluation
• Own the end-to-end RL workflow, including reward modeling, environment design, and test-time optimization
• Collaborate with research teams to translate emerging techniques into production-ready implementations

Requirements

• PhD in Computer Science, Computer Engineering, EECS, Mathematics, or related field (or BS/MS with strong research engineering background)
• Deep expertise in reinforcement learning and post-training
• Proven track record of building end-to-end ML pipelines and fine-tuning LLMs/code models
• Strong software engineering skills with experience in large-scale distributed systems and high-performance computing
• Proficiency with PyTorch, CUDA, QLoRA, or ZeRO
• Ability to prototype, benchmark, and productionize training pipelines

Preferred Qualifications

• Experience on post-training teams at frontier labs (e.g., OpenAI, Anthropic, DeepMind)
• Foundation in Electrical/Computer Engineering or Computer Architecture
• Publications in top ML (NeurIPS, ICLR, ICML) or EDA (DAC, ICCAD, DVCon) venues
• Experience as an early hire at an AI deeptech startup