Software Developer

Job Title: Machine Learning Engineer, Automated Scoring Team  

Location: Remote - US  

About Pearson’s Automated Scoring Team 

As the world's learning company, Pearson helps people make more of their lives through learning. We use our knowledge, passion, and reach to tackle the big problems in education and inspire a love of learning that lasts a lifetime. That is why we need smart people like you. Together, we can transform education and provide boundless opportunities for billions of learners worldwide.   

The Automated Scoring team develops machine learning-based models that analyze tens of millions of learner exam responses each year. Our technology is unique and meaningful, providing results quickly on student performance on standardized tests. The Machine Learning Engineer will join Pearson’s Automated Scoring Team to provide support for the administration of Pearson’s automated scoring programs and support the execution of initiatives to innovate and improve the delivery of Pearson's automated scoring technologies. This role will report to and work closely with the Director of Automated Scoring, but it will also support program managers, quality assurance automation engineers, psychometricians, and various internal stakeholders to ensure the quality and reliability of our automated scoring systems.  

Machine Learning Engineer’s Duties & Responsibilities  

Listed below are the typical duties and responsibilities expected of an individual for the job title. 

• 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 

Qualifications  

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. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.  

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