Senior Machine Learning Research Engineer

$140,000 - $150,000/Yr

Pearson Education - Springfield, IL

Full-time - Senior

Remote - Springfield, IL

1,001-5,000 employees

Publishing Industries

About the position

The Senior Machine Learning Research Engineer will play a pivotal role in advancing Pearson's research agenda around automated writing assessment. This position involves leading the design and development of machine learning and AI capabilities, collaborating with cross-functional teams, and contributing to the development of advanced systems that analyze and score learner exam responses. The role is fully remote, allowing for collaboration with a diverse team while making a significant impact on education through innovative technology.

Responsibilities

• Lead end-to-end design of machine learning and AI based capabilities
• Ideate, design, research and develop natural language processing and machine learning features, products and services
• Collaborate with cross-functional teams (e.g. software engineers, product managers, subject matter experts, learning scientists and interaction designers)
• Build and maintain software components (pipelines, APIs)
• Design experiments and build datasets to monitor, evaluate and improve new and existing ML/AI models and services
• Communicate model performance to technical and non-technical audiences
• Stay up-to-date and share latest advancements in natural language processing, machine learning and educational technology
• Publish research papers in machine learning and educational science conferences and journals
• Mentor others in best practices

Requirements

• A master's degree in a quantitative field (CS, EE, statistics, math) or equivalent work experience
• Four or more years with practical experience in developing natural language processing (NLP) and machine learning models
• A 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 (version control, object-oriented and functional programming, database and API access patterns, testing)
• A strong understanding of approaches to evaluating NLP and ML task performance
• Familiarity with cloud platforms and infrastructure (AWS, GCP, Azure) and distributed computing
• A dedication to ensuring equitable access to quality education and enhancing learning experiences for all students.

Nice-to-haves

• Familiarity with latest advancements in large language models (LLMs), generative AI, active learning and/or reinforcement learning
• Background in any of the following: education, learning sciences, cognitive science, 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)

Benefits

• Annual incentive program
• Remote work flexibility
• Opportunities for growth and development
• Inclusive culture and strong sense of belonging
• Commitment to diversity, equity, and inclusion