Applied AI Scientist (Small Language Model)

TL;DR

Applied AI Scientist (Small Language Model): Leads research and development for efficient, high-performance language models, with an accent on advancing model training techniques, optimizing architectures, and scaling AI solutions. Focus on designing, implementing, and evaluating experiments to improve model performance, robustness, and generalization while integrating AI safety and alignment principles.

Location: Hybrid role based out of San Francisco Bay Area, California, United States, requiring 3 days a week in the office.

Salary: $250,000.00 to $276,000.00

Company

hirify.global is the world’s leading API platform, used by over 40 million developers and 500,000 organizations.

What you will do

• Lead research and development of novel training methodologies and architectures for small and efficient language models.
• Design, implement, and evaluate model training experiments to improve performance, robustness, and generalization.
• Collaborate with research scientists and engineers on scalable training pipelines and model deployment strategies.
• Develop techniques for model compression, fine-tuning, and domain adaptation for real-world applications.
• Ensure AI safety, fairness, and alignment principles are integrated and evaluated rigorously.
• Partner with product teams to translate model capabilities into actionable features aligned with user needs.

Requirements

• Demonstrated experience in applied research or engineering roles focused on training language models, ideally small or efficient models.
• Strong programming skills in Python and familiarity with machine learning frameworks such as PyTorch, TensorFlow, or JAX.
• Deep understanding of language model architectures, training techniques, and optimization strategies.
• Experience with distributed training, data pipeline design, and scalable AI infrastructure.
• Passion for AI safety, interpretability, and delivering user-centered AI technology.
• Excellent communication skills with proven ability to collaborate across research, engineering, and product teams.

Nice to have

• Prior experience working with large and small language models in production or research settings.
• Background in reinforcement learning, prompt engineering, or transfer learning techniques.
• Experience with developer tools, APIs, or frameworks related to AI model integration and delivery.
• Knowledge of AI alignment, fairness, and ethical AI training methodologies.

Culture & Benefits

• Flexible schedule within a hybrid work model.
• Comprehensive benefits including full medical coverage, flexible PTO, wellness reimbursement, and a monthly lunch stipend.
• Wellness programs focused on physical and mental health.
• Frequent team-building events and a donation-matching program.
• Inclusive work culture focused on long-term growth and being the best version of themselves.