Pearson is the world's learning company, dedicated to transforming education and providing opportunities for learners globally. The Machine Learning Engineer will support the Automated Scoring Team by developing and maintaining machine learning models that analyze student exam responses, ensuring fair and unbiased scoring in real time.
Train, evaluate, and deploy machine learning models tasked with scoring short answer and essay student responses to formative and summative test administrations from school districts nationwide
Monitor performance of deployed machine learning models to ensure consistent, fair, and unbiased scoring in real time and recalibrate deployed models as needed
Maintain, update, and improve code base used to train and deploy machine learning models
Evaluate historical model performance and conduct experiments exploring strategies to potentially improve team modeling techniques and approaches
Research and stay up-to-date on emerging technologies in the NLP space
Qualification
Required
Bachelor’s degree in a quantitative field (CS, EE, statistics, math, data science)
0-2 years professional experience as a software engineer or data scientist
Solid understanding of machine learning principles and current/emerging technologies
Strong coding & analytics skills including proficiency in Python and Linux commands
Understanding of or experience with deploying machine learning models into production environments
Familiarity with software engineering fundamentals (version control, object-oriented and functional programming, database and API access patterns, testing)
Passionate about agile software processes, data-driven development, reliability, and systematic experimentation
Strong verbal and written communication skills including the ability to interact effectively with colleagues of varying technical and non-technical abilities
Curious and always learning habits of mind
Strong team-oriented approach to work, with excellent interpersonal and communication skills, both oral and written
Ability to work effectively as a member of a team in a collaborative environment
Demonstrated ability to manage multiple tasks and projects simultaneously
Preferred
Advanced degree in a quantitative field (CS, EE, statistics, math, data science)
Track record of producing machine learning models and production infrastructure at scale
Familiarity with traditional natural language processing (NLP) techniques and/or latest advancements in large language models (LLMs), generative AI, active learning and reinforcement learning
Strong experience with machine learning in non-NLP domains
Experience using containerized technologies such as Docker and/or Kubernetes
Benefits
Annual incentive program
Pearson operates as a media and education company that offers a wide range of services to its customers.
