Member of Technical Staff - ML Research

About the role

Architect is a frontier AI lab focused on chip design. We develop AI models and tools for creating custom Application-Specific Integrated Circuits (ASICs) at scale. Our mission is to collaborate between evolving machine learning workloads and custom hardware design, enabling new domains of technology beyond current capabilities.

Responsibilities

• Train AI models for chip design, verification, and exploration tasks.
• Develop and implement reinforcement learning environments and algorithms, including reward model training and experiment design.
• Design, build, and optimize robust pipelines for model fine-tuning and evaluation, ensuring theoretical performance translates to practical applications.
• Collaborate with research teams to translate advanced techniques into production-ready solutions and troubleshoot complex issues in training pipelines and model behavior.

Requirements

• PhD in Computer Science, Computer Engineering, EECS, Mathematics, or a closely related field, with specialization in Machine Learning, Deep Learning, or Artificial Intelligence.
• Strong background in reinforcement learning and post-training techniques, with experience deploying models in real-world settings.
• Experience in building and managing end-to-end ML pipelines, particularly in the context of reinforcement learning and fine-tuning large language models (LLMs).
• Expertise in systems engineering, including software development, large-scale distributed systems, high-performance computing, and distributed training frameworks like PyTorch, CUDA, QLoRA, and ZeRO.
• Ability to analyze and debug model training processes, balancing research exploration with engineering rigor and operational reliability.
• Proven ability to prototype, benchmark, and productionize training pipelines with rapid iteration cycles.
• Background in electrical/computer engineering, computer architecture, or chip design/verification processes, though not required.
• Publications in top-tier ML (NeurIPS, ICLR, ICML) or EDA (DAC, ICCAD, DVCon) conferences.
• Experience as a founding ML engineer/researcher or early hire at an AI/deep tech startup.

Qualifications

• BS/MS degree with a strong research engineering background in relevant fields.
• Experience working at frontier labs such as OpenAI, Anthropic, DeepMind, Mistral, MSL, Cohere, etc.
• Foundational knowledge in electrical/computer engineering, computer architecture, or chip design/verification processes (optional but beneficial).

Benefits

• Competitive salary and meaningful equity stake.
• Autonomy and visible impact within a fast-paced startup environment.
• Challenging and cutting-edge AI-driven chip design projects.

Pay

Details TBD.

Schedule

Details TBD.