Machine Learning Research Intern (AI)

Location: San Francisco, CA or New York, NY; available for a Summer 2027 internship with May/June start dates.

Salary: $120,000–$150,000 USD annual base salary for the full-time position; eligible roles may also include equity and benefits.

Company

Scale develops reliable AI systems, high-quality data, and full-stack technologies for enterprises, governments, and leading AI model developers.

What you will do

• Measure dangerous capabilities of frontier models and conduct preparedness research.
• Research benchmarks, model generalization, evaluation science, safety, alignment, and scalable oversight.
• Develop training, reinforcement learning, post-training, synthetic-data, and hybrid human-machine methods for difficult reasoning and high-stakes tasks.
• Improve production models through retraining and hyperparameter searches while preserving core model characteristics, then deploy the improvements.
• Create post-training and agentic solutions for enterprise and public-sector applications.
• Own technical research or production work that may be published or shipped, with mentorship from researchers and collaboration across industry and academia.

Requirements

• Currently enrolled in a BS, MS, or PhD program focused on Machine Learning, Deep Learning, or Natural Language Processing, with graduation in Fall 2027 or Spring 2028.
• Available for a Summer 2027 internship in San Francisco or New York, with a May or June start date.
• Prior research experience or a publication track record in LLMs, NLP, multimodal models, agents, safety, evaluation, alignment, or a related field.
• Experience with one or more general-purpose programming languages, including Python, JavaScript, or a similar language.

Nice to have

• Previous internship in Machine Learning, Deep Learning, Natural Language Processing, Adversarial Robustness, Alignment, Evaluation, or Agents.
• Research experience through internships, full-time roles, or work at a lab.
• Publications at top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, or AAAI, or contributions to open-source projects.
• Hands-on experience with reinforcement learning, agentic systems, or evaluation infrastructure.

Culture & Benefits

• Work across research, production machine learning, industry, and academia with mentorship from experienced researchers.
• Credos emphasize customer impact, cross-team collaboration, consistent quality, focused execution, frontier research, and anticipating downstream consequences.
• Benefits may include health, dental, and vision coverage, retirement benefits, a learning and development stipend, generous paid time off, and a commuter stipend.
• Eligible roles may include equity-based compensation.
• Scale is an inclusive equal opportunity workplace and provides reasonable accommodations for applicants with disabilities.

Hiring process

• Salary placement is determined during the interview process based on work location, skills, experience, qualifications, interview performance, and education or training.
• Candidates must wait 90 days before being reconsidered for the same role.