Machine Learning / Speech Engineer (Remote)

ELSA, Corp is a global leader in AI-powered English communication training. They are seeking a skilled applied Machine Learning Engineer to design, develop, and deploy core machine learning systems that enhance their personalized language learning experience.

Responsibilities:

• Develop and deploy machine learning models for ELSA's automated analysis of spoken proficiency
• Build and maintain machine learning systems to accurately track and model user proficiency across various English language skills
• Contribute to the research, development, and refinement of ELSA's adaptive learning system to create more personalized and effective learning paths
• Implement and manage robust evaluation frameworks to measure model performance, analyze user impact, and guide iterative improvements
• Collaborate cross-functionally with researchers, engineers, data scientists, and product teams to integrate ML models and features seamlessly into ELSA’s platform

Requirements:

• Solid understanding and practical experience with machine learning fundamentals (e.g., classification, regression, sequence modeling, evaluation metrics)
• Strong background in machine learning, preferably with experience or academic focus in speech processing or Natural Language Processing (NLP)
• Proficiency in Python and common ML/data science libraries (e.g., scikit-learn, Pandas, NumPy, PyTorch/TensorFlow)
• Strong software engineering skills, including experience with APIs, databases, testing, and software development best practices
• Experience working with data, including preprocessing, feature engineering, and analysis
• Master's or PhD degree in Computer Science, Machine Learning, Data Science, Electrical Engineering, or a related quantitative field, or equivalent practical experience
• Hands-on experience with Automatic Speech Recognition (ASR), Text-to-Speech (TTS) systems, or other speech processing techniques
• Experience developing NLP applications (e.g., text classification, sequence tagging, language modeling)
• Experience using Large Language Models (LLMs) for classification, feature extraction, or related tasks
• Experience with cloud stacks (e.g. AWS - including Dynamo, S3)