Machine Learning Engineer, Assessments

🕒 April 8

🏢🏡 San Francisco – Hybrid

💵 $220k - $300k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Speak

WebsiteLinkedInAll Job Openings

11 - 50 employees

📚 Education

🤖 Artificial Intelligence

👥 B2C

Education • Artificial Intelligence • B2C

Speak is a language learning app that utilizes advanced artificial intelligence to help users become fluent in a new language by getting them to speak out loud and receive instant feedback. It offers a virtual AI tutor that provides personalized curricula and allows users to practice on-the-go, at any time, and on various topics. With features such as AI-driven pronunciation correction and tailored study plans, Speak strives to make language learning interactive, accessible, and effective for millions of users worldwide.

📋 Description

• Ship and own assessment ML systems end-to-end • Build, deploy, and maintain scoring models/pipelines (feature extraction → model training → inference → feedback generation) • Own monitoring, regression tests, and ongoing iteration to maintain accuracy targets • Define and operationalize evaluation • Implement validation/evaluation frameworks for assessments, including metrics, test sets, and offline/online analysis • Translate assessment requirements into measurable acceptance criteria and guardrails • Partner deeply with the Assessment Design Lead • Co-develop the strategy, together with the Content team, to grow assessments into a core platform at Speak • Work in a tight weekly loop to deliver incremental improvement • Drive near-term delivery across products • Stand up or improve summative assessments (spoken language ability) and bring them reliably to production • Prototype and validate formative assessment approaches to measure improvement over weeks/months • Support data and labeling strategy • Help define data needs for training/evaluation (including psychometric measurement needs) • Build or improve pipelines that support label collection and analysis (especially for efficacy studies)

🎯 Requirements

• Domain expertise in spoken language proficiency assessment (linguistics, applied linguistics, pedagogy, or equivalent experience) • Strong experience designing and running evaluation + validation for assessment/scoring systems, and tailoring approaches to a specific product use case • 4+ years building automatic proficiency assessment systems (or equivalent depth in closely related scoring/evaluation domains) • PhD is helpful but not required • Proven ability to ship ML models to production (not only research), including reliability, monitoring, and iteration • Strong generalist ML/analysis skills (statistics, Python, PyTorch/model training) • Ability to operate cross-functionally and communicate clearly with non-technical partners (Content/LD, PM, leadership)

🏖️ Benefits

• Offers Equity