Machine Learning Research Engineer

Join Our Team as a Machine Learning Research Engineer

About the Role

Pearson is seeking a talented Machine Learning Research Engineer to join our Applied ML Research Team. This team is dedicated to maintaining and extending Pearson's leadership in automated writing analysis for various assessment product markets. As a Machine Learning Research Engineer, you will play a crucial role in advancing our research agenda around automated writing assessment. This is a fully remote position, allowing you to work from anywhere within the United States while collaborating with a diverse team.

Key Responsibilities

• Research and Development: Ideate, design, research, and develop natural language processing and machine learning features, products, and services.
• Collaboration: Work closely with cross-functional teams, including software engineers, product managers, subject matter experts, learning scientists, and interaction designers.
• Software Development: Build and maintain software components such as pipelines and APIs.
• Experimentation: Design experiments and build datasets to monitor, evaluate, and improve new and existing ML/AI models and services.
• Communication: Effectively communicate model performance to both technical and non-technical audiences.
• Innovation: Stay up-to-date with the latest advancements in natural language processing, machine learning, and educational technology.
• Publication: Publish research papers in machine learning and educational science conferences and journals.

Ideal Candidate Profile

• A master's degree in a quantitative field (CS, EE, statistics, math) or equivalent work experience.
• Two or more years of practical experience in developing natural language processing (NLP) and machine learning models.
• Proven track record in developing novel, AI/ML-backed solutions.
• Proficiency with deep learning techniques and common frameworks such as PyTorch or Tensorflow.
• Solid software engineering fundamentals, including version control, object-oriented and functional programming, database and API access patterns, and testing.
• Strong understanding of approaches to evaluating NLP and ML task performance.
• Familiarity with cloud platforms and infrastructure (AWS, GCP, Azure) and distributed computing.
• Dedication to ensuring equitable access to quality education and enhancing learning experiences for all students.

Bonus Qualifications

• Familiarity with the latest advancements in large language models (LLMs), generative AI, active learning, and/or reinforcement learning.
• Background in education, learning sciences, cognitive science, or psychometrics.
• Experience with automated scoring of writing, generation of feedback, and/or discourse analysis.
• Facility with containerized technologies such as Docker, Podman, and/or Kubernetes.
• Ability to utilize data creatively and effectively to define new machine learning tasks.
• Publication history in relevant conferences and workshops (ACL, NeurIPS, ICML, AAAI, AI in Education, Intelligent Tutoring Systems, LAK).

Compensation and Benefits

• The salary range for this position is between $120,000 and $130,000 per year.
• This position is eligible to participate in an annual incentive program.

Why Pearson?

Pearson is one of the 10 most innovative education companies of 2022. We are committed to creating vibrant and enriching learning experiences designed for real-life impact. We value the power of an inclusive culture and a strong sense of belonging. We promote a culture where differences are embraced, opportunities are accessible, and all individuals are supported in reaching their full potential.

Join us to make a significant impact on education while pushing the boundaries of what current technology can solve.