Machine Learning Engineer

Summary

Join Hugging Face, a rapidly growing platform for AI builders, and contribute to making cutting-edge speech-to-text and text-to-speech technologies more accessible to the open-source community. You will work on existing open-source libraries like Transformers, enhancing support for speech technologies and leading the creation of new audio ML libraries. This role involves fostering a vibrant machine learning community, interacting with researchers and practitioners, and contributing to open-source projects. Hugging Face values diversity and inclusivity, offering a supportive work environment with flexible hours, remote options, and comprehensive benefits.

Responsibilities

• Make cutting edge speech-to-text and text-to-speech technologies more accessible to the open-source community
• Work in existing open-source libraries, such as Transformers, boosting the support for robust speech-to-text, speaker diarization, text-to-speech
• Lead the creation of novel open-source libraries for ML in audio
• Foster one of the most active machine learning communities, helping users contribute to and use the tools that you build
• Interact with Researchers, ML practitioners and data scientists on a daily basis through GitHub, Discord, our forums, or Slack

Preferred Qualifications

Industry experience in speech recognition, speaker diarization, dialogue systems or text-to-speech

Benefits

• Reimbursement for relevant conferences, training, and education
• Flexible working hours and remote options
• Health, dental, and vision benefits for employees and their dependents
• Parental leave
• Flexible paid time off
• Company equity as part of their compensation package