Senior GenAI Research Scientist - AI Efficiency & Optimization (AI)

TL;DR

Senior GenAI Research Scientist (AI Efficiency & Optimization): Define and lead independent research agendas on foundation model efficiency in model training and reinforcement learning, with an accent on algorithmic innovations for large-scale neural network training or inference. Focus on driving optimizations for distributed training, memory efficiency, and compute efficiency through hands-on implementation and empirical validation.

Location: Mountain View, California or San Francisco, California

Salary: $166,000 — $230,000 USD

Company

hirify.global is the data and AI company relied on by over 10,000 organizations worldwide, including over 50% of the Fortune 500, to unify data, analytics, and AI on its Data Intelligence Platform.

What you will do

• Define and lead independent research agendas on foundation model efficiency in training and reinforcement learning, conducting experiments to validate hypotheses and benchmark against state-of-the-art.
• Drive algorithmic innovations for large-scale neural network training or inference, such as novel optimizers, low-precision techniques, and model adaptation methods.
• Optimize ML systems for distributed training, memory efficiency, and compute efficiency through hands-on implementation.
• Collaborate with researchers and engineers to advance the scientific frontier in deep learning and encode expertise into products for customer success with LLMs and AI systems.

Requirements

• MS/PhD in Computer Science or related field with strong foundations in machine learning and systems.
• Proven ability to write high-quality, efficient code in Python and PyTorch for research implementation and experimentation.
• Strong preference for first-author publications at top ML/systems conferences (ICLR, ICML, NeurIPS, MLSys) focused on optimization or efficiency.

Culture & Benefits

• Comprehensive benefits tailored to employee needs, including annual performance bonus, equity, and region-specific perks.
• Commitment to diversity, inclusion, and equal employment opportunity standards.
• Collaborative team environment with diverse backgrounds in research and engineering.