Research Engineer (AI/LLM)

Location: Seattle, Washington; expected to work from the Seattle offices

Salary: $128,880–$193,320 base salary per year, plus bonus plans

Company

hirify.global is a Seattle-based nonprofit AI research institute developing foundational AI research, large-scale open models, open datasets, and related artifacts.

What you will do

• Build infrastructure for next-generation large language model research.
• Design and implement systems for model architecture, training, evaluation, inference, and deployment.
• Develop scalable machine learning pipelines and optimize training and inference performance.
• Own features and experiments from conception through implementation and results presentation.
• Apply software engineering best practices in a research environment and collaborate with internal and external partners.
• Release contributions as open-source software, model releases, public APIs, datasets, and technical reports.

Requirements

• Bachelor’s degree in data science, computer science, electrical engineering, applied mathematics, statistics, machine learning, NLP, or a related field, or equivalent experience.
• 4+ years of experience building infrastructure for data preprocessing, model training, evaluation, inference, and deployment.
• Experience across the complete model development cycle, including dataset construction, tuning, performance profiling, and monitoring.
• Knowledge of modern deep learning, natural language processing, language models, and transformer architectures.
• Strong software engineering and debugging skills, with experience in Python and PyTorch, JAX, or TensorFlow.
• Familiarity with cloud computing resources such as AWS and containerization technologies such as Docker.

Nice to have

• Advanced degree or equivalent engineering experience.
• Contributions to open-source machine learning or research libraries.
• Experience operating models at scale in production or working in HPC environments.
• Curiosity about AI research.

Culture & Benefits

• Collaborative, transparent, and learning-focused research environment.
• Medical, dental, vision, life, disability, and employee assistance coverage for team members and families.
• 401(k), health savings and flexible spending account options.
• Paid sick leave, personal days, vacation, family leave, and holidays.
• Annual bonuses, long-term incentive plan, commuting or internet support, and fitness and wellbeing benefits.