AI Research Engineer, Enterprise Evaluations

Scale AI is seeking a technically rigorous and driven AI Research Engineer to join our Enterprise Evaluations team. This high-impact role is critical to our mission of delivering the industrys leading GenAI Evaluation Suite. You will be a hands-on contributor to the core systems that ensure the safety reliability and continuous improvement of LLM-powered workflows and agents for the enterprise.

The ideal candidate has a strong foundational knowledge of large language models a passion for tackling complex evaluation challenges and thrives in a dynamic fast-paced research environment. We are looking for an engineer who can think outside the box stays current with the latest literature in AI evaluation and is passionate about integrating novel research ideas into our workflows to build best-in-class evaluation systems.

Responsibilities

• Partner with Scales Operations team and enterprise customers to translate ambiguity into structured evaluation data guiding the creation and maintenance of gold-standard human-rated datasets and expert rubrics that anchor AI evaluation systems.
• Analyze feedback and collected data to identify patterns refine evaluation frameworks and establish iterative improvement loops that enhance the quality and relevance of human-curated assessments.
• Design research and develop LLM-as-a-Judge autorater frameworks and AI-assisted evaluation systems. This includes creating models that critique grade and explain agent outputs (e.g. RLAIF model-judging-model setups) along with scalable evaluation pipelines and diagnostic tools.
• Pursue research initiatives that explore new methodologies for automatically analyzing evaluating and improving the behavior of enterprise agents pushing the boundaries of how AI systems are assessed and optimized in real-world contexts.

Basic Qualifications

• Bachelors degree in Computer Science Electrical Engineering a related field or equivalent practical experience.
• 2 years of experience in Machine Learning or Applied Research focused on applied ML systems or evaluation infrastructure.
• Hands-on experience with Large Language Models (LLMs) and Generative AI in professional or research environments.
• Strong understanding of frontier model evaluation methodologies and the current research landscape.
• Proficiency in Python and major ML frameworks (e.g. PyTorch TensorFlow).
• Solid engineering and statistical analysis foundation with experience developing data-driven methods for assessing model quality.

Preferred Qualifications

• Advanced degree (Masters or Ph.D.) in Computer Science Machine Learning or a related quantitative field.
• Published research in leading ML or AI conferences such as NeurIPS ICML ICLR or KDD.
• Experience designing building or deploying LLM-as-a-Judge frameworks or other automated evaluation systems for complex models.
• Experience collaborating with operations or external teams to define high-quality human annotator guidelines.
• Expertise in ML research engineering stochastic systems observability or LLM-powered applications for model evaluation and analysis.
• Experience contributing to scalable pipelines that automate the evaluation and monitoring of large-scale models and agents.
• Familiarity with distributed computing frameworks and modern cloud infrastructure.

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 worlds most important decisions. Our products provide the high-quality data and full-stack technologies that power the worlds 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 Please see the United States Department of Labors Know Your Rights poster for additional information.

We comply with the United States Department of Labors Pay Transparency provision.

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