Machine Learning Engineer (Assessments)

Join our team as a Machine Learning Engineer (Assessments) and help build best-in-class assessment systems across multiple products. You will work closely with our Assessment Design Lead, Machine Learning, Product, and Engineering teams to turn assessment constructs and rubrics into reliable, scalable scoring and feedback systems. This role involves the implementation, deployment, and ongoing quality of our assessment algorithms and ML systems. You will also define and operationalize evaluation, partner with the Assessment Design Lead, and support data and labeling strategy.

• Implement, deploy, and maintain scoring models/pipelines for assessments, ensuring accuracy and reliability.
• Collaborate closely with the Assessment Design Lead and other stakeholders to translate assessment requirements into measurable acceptance criteria.
• Drive near-term delivery across products by standing up or improving summative assessments and prototyping formative assessment approaches.
• Ability to operate cross-functionally and communicate clearly with non-technical partners (Content/LD, PM, leadership)
• Strong experience designing and running evaluation + validation for assessment/scoring systems, and tailoring approaches to a specific product use case
• PhD is helpful but not required
• 4+ years building automatic proficiency assessment systems (or equivalent depth in closely related scoring/evaluation domains)
• Strong generalist ML/analysis skills (statistics, Python, PyTorch/model training)
• Domain expertise in spoken language proficiency assessment (linguistics, applied linguistics, pedagogy, or equivalent experience)
• Proven ability to ship ML models to production (not only research), including reliability, monitoring, and iteration
• Experience with speech/audio ML
• Experience with psychometrics concepts (reliability/validity, calibration)