Senior Principal AI Scientist - Foundation Models & Generative AI

• Extensive experience building and training large-scale transformer models from scratch.
• Deep expertise in modern deep learning, optimization theory, and representation learning.
• Strong understanding of transformer internals, including attention mechanisms, RoPE, ALiBi, GQA, and Mixture-of-Experts (MoE).
• Experience with distributed training frameworks including FSDP, ZeRO, tensor parallelism, and pipeline parallelism.
• Hands-on knowledge of mixed precision training (BF16, FP8), gradient checkpointing, and large-scale GPU clusters.
• Expertise with optimization algorithms including AdamW, Lion, Adafactor, learning-rate scheduling, and debugging training instability.
• Strong understanding of scaling laws, compute vs. data tradeoffs, and efficient model scaling.
• Experience with modern alignment techniques such as RLHF, DPO, or GRPO is highly desirable.

Pulled from the full job description

• Health insurance
• Retirement plan
• Paid time off
• Vision insurance
• Dental insurance
• Disability insurance

• Paid holidays, Remote (U.S.) | Full-Time | $185,000-$280,000 + Bonus + Equity We’re partnering with an industry-leading AI technology company that has deployed its technology at massive global scale and is building the next generation of foundation models powering intelligent, real-world systems. This is an opportunity to join a world-class research organization where you’ll shape core model architecture, drive technical strategy, and solve some of the hardest problems in modern AI. If you’ve trained large language models from scratch-not simply fine-tuned existing models-and enjoy solving deep optimization and scaling challenges, we’d love to connect. What You’ll Do

• Design and train large-scale transformer and foundation models from the ground up.
• Own architectural decisions across language, multimodal, and emerging model architectures.
• Lead research into optimization, scaling laws, and training stability for production-scale models.
• Develop novel approaches for model efficiency, convergence, and inference performance.
• Partner closely with ML systems engineers while maintaining ownership of model architecture and research direction.
• Influence the long-term technical roadmap for next-generation generative AI systems., You’ll Solve Problems Like
• Preventing training divergence at extreme model scale.
• Designing architectures that improve convergence and generalization.
• Optimizing compute efficiency without sacrificing model quality.
• Building scalable multimodal and hybrid foundation model architectures.
• Advancing state-of-the-art generative AI capabilities for production environments.

Compensation & Benefits

• Base Salary: $185,000-$280,000
• Annual performance bonus
• Equity opportunity
• Comprehensive medical, dental, and vision coverage
• Life and disability insurance
• Generous PTO and paid holidays
• Retirement benefits
• Remote work flexibility (role dependent)