Machine Learning Research Internship – Summer 2026

Job Description

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About the Job: Machine Learning Research Internship – Summer 2026

At Scale AI, our Machine Learning Research team is at the forefront of building the foundational technologies for the next generation of AI systems. We are dedicated to pushing the boundaries of what is possible with frontier models while rigorously ensuring their safety, reliability, and alignment. Our innovative work spans a critical array of research domains, including: generative AI, advanced post-training methods, scalable oversight, synthetic data pipelines, red teaming, and evaluation science.

We are actively developing a large-scale hybrid human-machine system designed to power sophisticated machine learning pipelines for dozens of industry-leading customers. These cutting-edge models and systems are central to Scale’s long-term strategic vision, enabling the processing of billions of tasks monthly and supporting some of the most complex and advanced use cases across the entire AI ecosystem.

As an intern, you will be immersed in a dynamic environment, working on a compelling combination of deeply technical ML applications in production and engaging in cutting-edge research problems. This role offers significant opportunities to collaborate with leading research teams across both industry and academia, fostering a truly enriching learning experience.

Example Projects You Might Work On:

• Dangerous Capabilities & Preparedness: Measuring the dangerous capabilities of frontier models and conducting preparedness research to mitigate potential risks.
• Benchmark Innovation: Researching the science behind and creating new, robust benchmarks specifically designed for evaluating frontier models.
• Advanced Reasoning: Researching and developing novel methods for training models to excel on extremely difficult reasoning problems that necessitate long chains of thought.
• Scalable Oversight Protocols: Investigating and implementing scalable oversight protocols that empower humans to produce and quality control reasoning chains that extend beyond their native cognitive capabilities.
• Model Generalization & Capabilities: Studying the boundaries of model generalization and capabilities to inform data-driven advancements and improvements.
• Synthetic & Hybrid Data: Conducting research on synthetic data generation and hybrid data approaches with humans in the loop to significantly scale up the creation of high-quality training data.
• Production Model Optimization: Taking existing production models, identifying areas for improvement, enhancing them through retraining and hyperparameter searches, and then deploying these improvements without regressing on core model characteristics.
• Post-Training & Agentic Solutions: Creating advanced post-training or agentic solutions that seamlessly integrate into our ability to deliver innovative applications for our enterprise clients.

Required Qualifications:

• Academic Standing: Currently enrolled in a BS, MS, or PhD program with a dedicated focus on Machine Learning, Deep Learning, Natural Language Processing, or Computer Vision.
• Graduation Date: Expected graduation in Fall 2026 or Spring 2027.
• Research Experience: Prior experience or a demonstrable track record of research publications in areas such as LLMs, NLP, Multimodal AI, agents, safety, evaluation, alignment, or a related field.
• Programming Proficiency: Experience with one or more general-purpose programming languages, including but not limited to: Python, Javascript, or similar.
• Communication: Ability to speak and write fluently in English.
• Availability: Must be available for a Summer 2026 internship (May/June starts).

Ideally You’d Have:

• Previous Internships: Prior internship experience in fields such as Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Adversarial Robustness, Alignment, Evaluation, or Agent-based AI.
• Researcher Experience: Experience as a researcher, whether through previous internships, full-time roles, or work at a research lab.
• Publications/Contributions: Publications in top-tier journals or conferences such as NeurIPS, ICML, ICLR, CVPR, AAAI, or significant contributions to open-source projects.

About Us:

At Scale, our fundamental mission is to develop reliable AI systems for the world’s most critical decisions. Our product suite delivers the high-quality data and full-stack technologies that power the globe’s leading AI models. We empower enterprises and governments to successfully build, deploy, and oversee AI applications that generate real, measurable impact. We collaborate closely with industry titans like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and vital U.S. government agencies including the Army and Air Force. We are continuously expanding our team to accelerate the development of transformative AI applications.

We are deeply committed to fostering an inclusive and equal opportunity workplace where everyone can bring their whole selves to work. We believe in equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity, or Veteran status.