Senior Machine Learning Research Engineer

United States

Pearson

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Job Title: Senior Machine Learning Research Engineer 

Location: Remote 

 

About Us 

 

At Pearson, we're dedicated to transforming education through innovative solutions. As a global leader in learning, we leverage our expertise, passion, and extensive reach to address complex educational challenges and foster a lifelong love of learning. We're seeking talented individuals like you to join our mission. Together, we can revolutionize education and create opportunities for billions of learners worldwide. 

 

The Applied ML Research Team is focused on maintaining and extending Pearson's leadership in automated writing analysis for formative, interim, and summative assessment product markets.  Together with our Operational Delivery and ML Platform teams, we develop advanced machine learning systems that analyze and score tens of millions of learner exam responses annually.  Our technology delivers quick, meaningful insights into student performance on standardized tests, supporting educators, students, and parents in their teaching and learning journeys.  Join us to make a significant impact on education while pushing the boundaries of what current technology can solve. 

 

Job Description 

 

We are “full stack” researchers who take end-to-end responsibility for research and development of machine learning capabilities.  As a Machine Learning Research Engineer, you will play a key 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. 

 

In this role you will: 

  • 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 

 

An ideal candidate will have: 

  • 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. 
  • Bonus Qualifications: 
  • 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) 

We understand that not every candidate will meet all these qualifications. If you are excited about this role and our mission, we encourage you to apply. We are committed to finding the right person for our team and providing opportunities for growth and development. 

Compensation at Pearson is influenced by many factors including skill set, level of experience, and specific location. As required by the Colorado, California, Washington State, New York State and New York City laws, the pay range for this position is as follows: 

The minimum full-time salary range is between $140k - $150k  

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

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Tags: APIs AWS Azure Deep Learning Docker Engineering GCP Generative AI ICML Kubernetes LLMs Machine Learning Mathematics ML models NeurIPS NLP Pipelines PyTorch Reinforcement Learning Research Statistics Teaching TensorFlow Testing

Perks/benefits: Career development Conferences Salary bonus

Regions: Remote/Anywhere North America
Country: United States

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