Pearson's Automated Scoring Team needs to develop and deploy machine learning models to analyze millions of learner exam responses annually, providing quick and reliable results on student performance on standardized tests. The Machine Learning Engineer will support the administration and innovation of these automated scoring programs.
Requirements
- 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)
- 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
Responsibilities
- 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
Other
- Qualified individuals will be required to work with dynamic teams driven by project delivery goals.
- They should possess the drive to learn and continuously improve on work performance.
- They must also be detail-oriented and eager to work with peers in producing quality output.
- Strong verbal and written communication skills including the ability to interact effectively with colleagues of varying technical and non-technical abilities
- Ability to work effectively as a member of a team in a collaborative environment
