- he successful candidate will implement, test, optimize and deploy multimodal generative foundation models with a focus on the audio modality.
- Design, implement, and maintain data pipelines for various purposes
- Demonstrate proficiency in generative AI techniques, including familiarity with LLM models
- Establish best practices in software engineering applied to generative AI
- Keep up to date with emerging AI trends, tools, and frameworks.
- Manage codebase using version control systems like Gitlab (or Git)
- Ensure AI solutions adhere to security and privacy standards. Address data privacy risks, model vulnerabilities, and ethical considerations.
- Create detailed architecture documentation, including diagrams, flowcharts, and technical specifications.
- Open sourcing and publication.
Qualifications and Experience
To qualify for this position, you will need to meet the following requirements:
- Master’s degree in Computer Science, Computer Engineering (or equivalent) with 5+ years of experience in architecting, designing, developing, and deploying AI solutions.
- Expertise in audio related fields: audio (speech, sound, or music) generation, text-to-speech (TTS) synthesis, text-to-music generation, text-to-sound generation, speech recognition, speech / audio representation learning, video-to-audio generation, audio-visual learning, audio language models, lip sync, etc.
- Experienced in one of the following popular ML frameworks: Pytorch, Tensorflow.
- Proficiency in Python programming language.