Remote Machine Learning Engineer (Voice Cloning and Speech Synthesis)

Description:

• Factored is seeking an experienced Machine Learning Engineer with expertise in text-to-speech (TTS) models and voice cloning technologies.
• The role involves developing and optimizing ML models to enhance user experience for voice actors generating content in multiple languages.
• Responsibilities include designing, developing, and optimizing TTS models while maintaining the style and authenticity of original voice actors.
• The engineer will implement real-time, scalable voice cloning systems with under 1-second inference time.
• Collaboration with teams on audio datasets, including voice recordings and multilingual transcriptions, is essential.
• The position requires experimentation with models like StyleDiffusion and exploring advanced approaches for realistic speech synthesis.
• Ensuring performance reliability across millions of users by scaling systems for high-demand scenarios is a key task.
• The engineer will handle audio data preparation, including splitting, up/downsampling, and file management using tools like Whisper.
• Integration of models into a cloud environment (e.g., AWS) for deployment and monitoring is also part of the role.

Requirements:

• Candidates must have strong proficiency in Python and experience with machine learning frameworks such as TensorFlow or PyTorch.
• Proven expertise in speech synthesis models and TTS technologies, focusing on realistic, human-like outputs, is required.
• Experience with voice cloning and familiarity with models like StyleDiffusion or similar is necessary.
• The ability to deliver real-time solutions with high-performance reliability in production environments is essential.
• Experience working with audio datasets, including data preprocessing, splitting, upsampling/downsampling, and file management, is required.
• Familiarity with multilingual models and working with transcriptions in multiple languages is expected.
• Proficiency in cloud platforms like AWS and experience deploying machine learning models in production environments is necessary.
• Experience with Whisper or similar tools for handling audio datasets is required.
• Knowledge of traditional ML techniques, including XGBoost or gradient boosting for model optimization, is a plus.

Benefits:

• Factored offers a transparent workplace where every employee has a voice in building the company.
• The company is committed to investing in employees' career and professional growth in meaningful ways.
• Employees are encouraged to work with passionate and intelligent colleagues, fostering a collaborative environment.
• The company values honesty, diligence, and kindness, creating a positive workplace culture.
• Employees have opportunities for learning and growth based on merit, not just experience.
• Factored promotes a fun and engaging work environment, with activities such as making music, playing sports, and hosting parties.