AI/ML Engineer at Tamber

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Requirements:

• 3+ years of hands-on experience developing machine learning models for production.
• Strong Python skills, including experience with PyTorch, TensorFlow, or JAX.
• Experience with vector models and LoRA-fied RAG models for efficient retrieval and processing.
• Expertise in audio files, MIDI processing, and signal processing techniques.
• Familiarity with gestural recognition, hand tracking, and face identification models.
• Experience with multimodal AI models (text + audio + vision).
• Strong engineering fundamentals—ability to write production-grade ML code, work with Git, and follow best practices in model deployment.
• Ability to work independently and own complex AI features from research to production deployment.
• A deep passion for music and technology, with an understanding of music structure, DAWs, or composition.

Responsibilities:

• Architect, train, and deploy large-scale machine learning models for music analysis, discovery, and AI-assisted workflows.
• Develop and optimize vector models and LoRA-fied RAG models for efficient music-related AI applications.
• Work on gesture recognition models for intuitive music control (e.g., hand tracking, facial identification for personalized interactions).
• Work on AI-driven music discovery models, enabling search through audio, MIDI, lyrics, and abstract emotional descriptors.
• Design robust training pipelines for audio and MIDI-based AI models.
• Ensure seamless integration of AI models with Tamber’s backend and frontend systems.
• Write high-quality, scalable code and contribute to the core repositories (Git, CI/CD workflows, and production-ready model deployment).
• Optimize inference times and memory usage to ensure real-time performance across different devices.
• Research and implement the latest advancements in AI for music, keeping Tamber at the forefront of innovation.