Large Language Model Analyst Jobs (NOW HIRING)

Natural Language Specialist, Educational Measurement & AI

College Board -Learning & Assessment

Location:

• This is a remote role. Candidates who live near CB offices have theoptionof being fully remote or hybrid (Tuesday and Wednesday in office). All CB employeesare required tooccasionally travel to meet in person for business purposes.
  

Role Type:

• This is a full-time position

About the Team

The Automated Scoring team provides critical insights and tools to support the design, delivery, and continuous improvement of digital assessments. Weoperateat the intersection of educational measurement, data science, and emerging AI technologies. Our work spans the measurement of language-based constructs, the development of large language model (LLM) systems for feedback generation and annotation, and research to ensure the validity, fairness, and reliability of our systems.

We are a collaborative, mission-driven team that values both psychometric rigor and technicalexpertise. We combine modern machine learning approaches, including large language models, with strong measurement principles to create scalable, trustworthy solutions that expand opportunity for students.

About the Opportunity

As a Natural Language Specialist, you will help define and advance how language-based performance is measured in high-stakes educational settings. This role sits at the intersection of natural language processing, large language models, and educational measurement, and is ideal for someone whopairsstrong measurement training with a working knowledge of modern AI.

You will translate measurement constructs into LLM-based feedback and annotation systems, design and conduct the studies thatestablishtheir validity, fairness, and reliability, and ensure that what our models produce holds up to rigorous psychometric standards.You will serve as the measurement authority for cross-functional partners-psychometricians, engineers, and data scientists-shaping how language-based constructs are defined, evaluated, and applied across theteam's portfolio of systems.Your primary lens will be measurement: defining what feedback and annotations mean,evidencingthat they mean it, and improving them over time.

In this role, you will:

Natural Language Measurement & Psychometrics(40%)

• Define and operationalize language-based constructs for automated annotation and feedback generation

• Apply psychometric principles-reliability, validity, dimensionality, and measurement invariance-to LLM-based feedback and annotation systems

• Design and lead validity studies, including human-machine agreement, rater comparison, and fairness analyses across subgroups

• Develop and apply methods for detecting and mitigating bias in language-based scores

• Establish/Recommendannotation guidelines, feedback quality criteria, and standards for acceptable model performance

• Translate measurement requirements into specifications that guide model development and evaluation
  

LLM & AI Development(30%)

• Contribute to prompt design, fine-tuning, and evaluation of LLM-based feedback and annotation systems

• Develop and refine machine learning models for measuring language-based constructs

• Build evaluation frameworks that connect model behavior to measurement outcomes

• Collaborate with senior team members to translate measurement findings into production systems

• Implement high-quality, maintainable code for model development and evaluation
  

Research & Validation(10%)

• Lead and contribute to research studies that evaluate model performance and support assessment validity

• Apply statistical and psychometric methods to analyze results and inform model improvements

• Document methodologies and findings in a clear and rigorous manner

• Stay current with advances in educational measurement, NLP, and learning science
  

Data Engineering & Pipelines(10%)

• Prepare and curate datasets for measurement studies and model evaluation

• Support reproducible data processing workflows for training, evaluation, and monitoring

• Partner with engineers to integrate feedback and annotation models into scalable systems
  

Team Operations & Collaboration(10%)

• Collaborate closely with psychometricians, data scientists, and engineers

• Contribute to documentation, methodological standards, and team best practices

• Participate in peer reviews and knowledge sharing

• Actively raise the measurement literacy of the broader team-mentoring junior ICs, providing technical feedback on colleagues' work, and building shared standards

About You

You bring strong measurement training and a genuine interest in how modern AI can be used to measure language-based performance. You are excited about applying psychometric rigor to large language models in high-stakes educational settings.

You have:

• AMaster'sor PhD (or near completion) in a quantitative field such as Psychometrics, Educational Measurement, Quantitative Psychology, Statistics, Data Science, or a related discipline (measurement-focused training strongly valued)

• A solid foundation in measurement theory, including reliability, validity, and fairness; familiarity with IRT, generalizability theory, or related frameworks is highly desirable

• Experience analyzing language or text data, with exposure to NLP or large language models

• Programming skills in Python and familiarity with data science libraries (e.g., pandas, NumPy,PyTorch)

• Demonstrated ability to conduct rigorous research (e.g., thesis, publications, or applied research projects)

• Strong skills in statistical analysis and experimental design

• Familiarity with working with structured and unstructured data

• Strong attention to detail and a commitment to producing high-quality, reproducible work

• The ability to travel5-10times a year to College Board offices or on behalf of College Board business.
  

You are:

• Curious and eager to learn new tools, methods, and domains

• Thoughtful about the implications of AI systems, including fairness and validity

• Able to communicate technical and measurement concepts clearly to diverse audiences

• Comfortable working in a collaborative, cross-functional environment

• Motivated by mission-driven work in education
  

All roles at College Board require:

• A passion for expanding educational and career opportunities and mission-driven work

• Curiosity and enthusiasm for emerging technologies, with a willingness to experiment with and adopt new AI-driven solutions and comfort with learning and applying new digital tools independently and proactively.

• Clear and concise communication skills, written and verbal

• A learner's mindset and a commitment to growth: welcoming diverse perspectives, giving and receivingtimely, respectful feedback, and continuously improving through iterative learning and user input.

• A drive for impact and excellence: solving complex problems, making data-informed decisions, prioritizing what matters most, and continuously improving through learning, user input, and external benchmarking.

• A collaborative and empathetic approach: working across differences, fostering trust, and contributing to a culture of shared success

• Authorization to work in the United States

About Our Process

• Application review will beginimmediatelyand will continue until the position is filled.This role is expected to accept applications for a minimum of 5 business days.

• Whilethehiring processmay vary, it generallyincludes:resume and application submission, recruiter phone/video screen, hiring manager interview, performance exercise such as live coding, a panel interview, a conversation with leadership and reference checks.

What We Offer

AtCollegeBoard, we offer more than a paycheck- we provide a meaningful career, a supportive team, and a comprehensive package designed to help you thrive.We'rea self-sustaining nonprofit that believes in fair and competitive compensation grounded in your qualifications, experience, impact, and the market.

A Thoughtful Approach to Compensation

• The hiring range for this role is $88,000-$145,000.

• Your exact salary will depend on your location, experience, and how your background compares to others in similar roles at the College Board.

• We aim to make our best offer upfront, rooted in fairness, transparency, and market data.

• We adjust salaries by location to ensure fairness, no matter where you live.
  

You'llhave open, transparent conversations about compensation, benefits, and whatit'slike to work atCollegeBoard throughout your hiring process. Check outourcareers pageformore.