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.

• 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

Desirable

• Bachelor’s degree in a quantitative field (CS, EE, statistics, math, data science)

Experiences That Will Set You Apart

• 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

Working location and trave l

This position is remote.

Willingness to travel as necessary.

Compensation at Pearson is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific location. As required by the California, Colorado, Hawaii, Maryland, New York State, New York City, Washington State, and Washington DC laws, the pay range for this position is as follows:

The minimum full-time salary range is between $90,000 - $110,000.

This position is eligible to participate in an annual incentive program, and information on benefits offered is here.

What to expect from Pearson

Did you know Pearson is one of the 10 most innovative education companies of 2022?

At Pearson, we add life to a lifetime of learning so everyone can realize the life they imagine. We do this by creating vibrant and enriching learning experiences designed for real-life impact. We are on a journey to be 100 percent digital to meet the changing needs of the global population by developing a new strategy with ambitious targets. To deliver on our strategic vision, we have five business divisions that are the foundation for the long-term growth of the company: Assessment & Qualifications, Virtual Learning, English Language Learning, Workforce Skills and Higher Education. Alongside these, we have our corporate divisions: Digital & Technology, Finance, Global Corporate Marketing & Communications, Human Resources, Legal, Strategy and Direct to Consumer. Learn more at We are Pearson.

We value the power of an inclusive culture and also a strong sense of belonging. We promote a culture where differences are embraced, opportunities are accessible, consideration and respect are the norm and all individuals are supported in reaching their full potential. Through our talent, we believe that diversity, equity and inclusion make us a more innovative and vibrant place to work. People are at the center, and we are committed to building a workplace where talent can learn, grow and thrive.

Pearson is an Affirmative Action and Equal Opportunity Employer and a member of E-Verify. We want a team that represents a variety of backgrounds, perspectives and skills. The more inclusive we are, the better our work will be. All employment decisions are based on qualifications, merit and business need. All qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We strive for a workforce that reflects the diversity of our communities.

To learn more about Pearson’s commitment to a diverse and inclusive workforce, navigate to: Diversity, Equity & Inclusion at Pearson.

If you are an individual with a disability and are unable or limited in your ability to use or access our career site as a result of your disability, you may request reasonable accommodations by emailing TalentExperienceGlobalTeam@grp.pearson.com.

Note that the information you provide will stay confidential and will be stored securely. It will not be seen by those involved in making decisions as part of the recruitment process.

Job: TECHNOLOGY

Organization: Assessment & Qualifications

Schedule: FULL_TIME

Workplace Type: Remote

Req ID: 17682