採用
Required Skills
Python
Machine Learning
Deep Learning
LLMs
At Scale, our Machine Learning Research team is focused on building the foundation for the next generation of AI systems—pushing the boundaries of what’s possible with frontier models while ensuring safety, reliability, and alignment at every step. Our work spans across generative AI, advanced post-training methods, scalable oversight, synthetic data pipelines, red teaming, and evaluation science.
We are developing a large-scale hybrid human-machine system to power machine learning pipelines for dozens of industry-leading customers. These models and systems form the backbone of Scale’s long-term strategy, enabling billions of tasks monthly and supporting some of the most complex and advanced use cases in the AI ecosystem.
You’ll be working on a combination of deeply technical ML applications in production and cutting-edge research problems, with the opportunity to collaborate with leading research teams across industry and academia.
Example Projects
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Measuring the dangerous capabilities of frontier models and conducting preparedness research
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Research on the science and creation of new benchmarks for frontier models
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Research and develop new methods for training models to excel on extremely difficult reasoning problems that require long chains of thought
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Research scalable oversight protocols that enable humans to produce and quality control reasoning chains beyond their native capabilities
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Studying the boundaries of model generalization and capabilities to inform data-driven advancements.
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Research on synthetic data and hybrid data with humans in the loop to scale up high-quality data generation.
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Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics.
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Create post-training or agentic solutions that integrate into our ability to deliver applications for our enterprise clients
Required to have:
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Currently enrolled in a BS/MS/PhD Program with a focus on Machine Learning, Deep Learning, Natural Language Processing or Computer Vision with a graduation date in Fall 2026 or Spring 2027
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Prior experience or track record of research publications on LLMs, NLP, Multimodal, agents, safety, evaluation, alignment or a related field
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Experience with one or more general purpose programming languages, including: Python, Javascript, or similar
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Ability to speak and write in English fluently
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Be available for a Summer 2026 (May/June starts) internship
Ideally you’d have:
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Have had a previous internship around Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Adversarial Robustness, Alignment, Evaluation and Agent
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Experience as a researcher, including internships, full-time, or at a lab
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Publications in top-tier journals such as NeurIPS, ICML, ICLR, CVPR, AAAI, etc. or contributions to open source projects
**PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
*We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to 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. *
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.
*We comply with the United States Department of Labor's Pay Transparency provision. *
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
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About Scale AI

Scale AI
Series CAccelerate the development of AI applications.
501-1,000
Employees
San Francisco
Headquarters
$7.3B
Valuation
Reviews
3.5
2 reviews
Work Life Balance
1.5
Compensation
3.5
Culture
2.0
Career
3.0
Management
1.5
25%
Recommend to a Friend
Pros
Famous in tech world
Good for career transitions
Offers equity after 1 year
Cons
Extremely long working hours (80+ per week)
Unprofessional recruiting process
Poor communication during hiring
Salary Ranges
0 data points
Junior/L3
L3
Junior/L3 · Data Scientist L3
0 reports
$123,049
total / year
Base
-
Stock
-
Bonus
-
$104,592
$141,506
Interview Experience
5 interviews
Difficulty
3.2
/ 5
Duration
14-28 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 60%
Negative 20%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Technical Interview
5
Final Round
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
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