Founding Member of Technical Staff - ML Infra

About the Company

Architect is a frontier AI research and product lab for chip design. Born out of Stanford, our team blends researchers and engineers from Anthropic, Google DeepMind, NVIDIA, Meta SuperIntelligence Labs, Apple, and Intel to reimagine chip design using AI.

Responsibilities

• Build, maintain, and improve algorithms and engineering systems used to post-train models for chip designs
• Profile reinforcement learning and training pipelines to detect bottlenecks and implement optimizations
• Collaborate with ML researchers to implement stable and fast versions of new finetuning recipes like RLHF/SFT
• Focus on improving training speed and reliability

Requirements

• PhD in Computer Science, EECS, Mathematics, or related field (or BS/MS with strong research engineering background)
• Proven track record of building end-to-end ML pipelines including data curation and large-scale LLM finetuning
• Expertise in diagnosing training slowdowns and building instrumentation for distributed environments
• Results-oriented mindset with a bias towards flexibility and impact

Preferred Qualifications

• Experience implementing LLM finetuning algorithms and modifying systems based on model architectures
• Previous experience at frontier labs such as OpenAI, Anthropic, DeepMind, Mistral, or Cohere
• Foundation in Electrical/Computer Engineering and chip-design processes
• Publications in top ML (NeurIPS, ICLR, ICML) or Systems (OSDI, SOSP) venues
• Experience as a Founding Engineer or early hire at an AI deeptech startup

Benefits

• Competitive salary and meaningful equity stake
• Fast-paced startup with autonomy and visible impact
• Cutting-edge AI-driven chip design challenges