Machine Learning Engineer, Speech & Multimodal Language Modeling

What you'll do

• Design and implement processes for evaluating and improving multi-modal generative models.
• Process large-scale speech audio data for foundation model training in coordination with Data Engineers.
• Fine-tune Large Language Models (LLMs) and Speech Language Models (SpeechLMs) for specific use cases.
• Define evaluation criteria and methodologies to systematically evaluate foundation models.
• Design experiments to test the performance of models and systems under test.
• Conduct robust statistical analysis to identify model deficiencies and failure states.

What we're looking for

• Master's degree in Computer Science or Machine Learning.
• PhD in Computer Science, Machine Learning, Statistics, or another STEM field is preferred.
• 2+ years of hands-on experience building and evaluating generative AI models.
• 5+ years of hands-on experience with SpeechLMs or LLMs is preferred.
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Experience processing large-scale audio data on distributed systems.
• Experience with prompt evaluation, optimization, and fine-tuning of foundation models.
• A track record of publications or technical presentations in Machine Learning journals or conferences.