Job Description
We are seeking a visionary Lead AI Architect to spearhead the development of our next-generation generative AI models. As we prepare for the rapid evolution of the 2026 AI landscape, you will be responsible for designing scalable, high-performance infrastructure that powers our flagship products. This is an opportunity to work on cutting-edge Large Language Models (LLMs), multimodal systems, and autonomous agents that redefine human-computer interaction. If you are passionate about pushing the boundaries of artificial intelligence and possess deep technical expertise, we want to hear from you.
Why Join Us?
- Work at the forefront of AI innovation in the heart of San Francisco.
- Competitive compensation package including equity.
- Flexible hybrid work environment.
- Access to state-of-the-art compute resources and research tools.
Responsibilities
- Architecture Design: Design and implement robust, scalable architectures for training and serving large-scale generative AI models (transformers, diffusion models).
- Model Optimization: Lead efforts in model compression, quantization, and inference optimization to ensure low-latency deployment on edge and cloud devices.
- R&D Leadership: Conduct cutting-edge research to explore emerging techniques in reinforcement learning, causal inference, and synthetic data generation.
- Team Mentorship: Mentor a team of senior machine learning engineers and data scientists, fostering a culture of technical excellence and innovation.
- System Integration: Collaborate with product and engineering teams to integrate complex AI models into real-world applications seamlessly.
- Strategic Planning: Define technical roadmaps and evaluate new technologies to ensure our stack remains future-proof for the 2026 era.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Physics, or a related field with a focus on Machine Learning or Artificial Intelligence.
- Experience: 5+ years of professional experience in machine learning engineering, with at least 2 years in a lead or architect role.
- Technical Skills: Deep expertise in PyTorch, TensorFlow, or JAX; experience with distributed training frameworks (Ray, MPI, Horovod).
- Modeling: Proven track record of training and fine-tuning state-of-the-art LLMs (GPT, LLaMA, Claude architectures).
- Software Engineering: Strong proficiency in Python, C++, and cloud infrastructure (AWS, GCP, or Azure).
- Problem Solving: Ability to tackle complex engineering challenges involving large-scale data pipelines and GPU clusters.