Research Engineer (AI)

TL;DR

Research Engineer (AI): Developing next-generation large language models with an accent on model architecture, algorithms, and training infrastructure optimization. Focus on designing, running, and analyzing scientific experiments, scaling distributed training, and building safe, steerable AI systems.

Location: Hybrid with at least 25% office presence in San Francisco, USA

Salary: $340,000 - $425,000 USD annually

Company

hirify.global is a public benefit corporation focused on creating reliable, interpretable, and steerable AI systems that are safe and beneficial for society.

What you will do

• Conduct research and implement solutions in model architecture, algorithms, data processing, and optimizer development
• Lead small research projects independently and collaborate on larger initiatives
• Design, run, and analyze experiments to advance understanding of large language models
• Optimize and scale training infrastructure for efficiency and reliability
• Develop and improve developer tooling to enhance productivity
• Contribute across the stack from low-level optimizations to high-level model design

Requirements

• Must have at least a Bachelor's degree or equivalent experience
• Strong software engineering skills and experience with Python and deep learning frameworks (PyTorch preferred)
• Experience with large-scale machine learning and language models
• Ability to balance research goals with practical engineering constraints
• Excellent communication skills and collaborative mindset
• Hybrid work with minimum 25% office presence in San Francisco
• Visa sponsorship available but not guaranteed for all candidates

Nice to have

• Experience with high-performance, large-scale ML systems
• Familiarity with GPUs, Kubernetes, and OS internals
• Knowledge of transformer architectures and reinforcement learning
• Background in large-scale ETL processes

Culture & Benefits

• Competitive compensation including equity and benefits
• Generous vacation and parental leave
• Flexible working hours and hybrid work policy
• Inclusive and diverse workplace encouraging applications from underrepresented groups
• Collaborative team environment with frequent research discussions

Hiring process

• Application review including evaluation of research and engineering skills
• Interviews focusing on technical expertise and communication
• Discussions on alignment with AI safety and ethical considerations