Gen AI Audio Researcher

Job not on LinkedIn

🕒 February 25

🇬🇧 United Kingdom – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

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Brahma

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

₿ Crypto

💳 Fintech

🔌 API

💰 $4.2M Seed Round - Brahma on 2022-02

Crypto • Fintech • API

Brahma is a developer-focused orchestration layer that connects onchain financial logic to offchain payment and settlement systems. It enables programmable capital flows across blockchains, strategies, and traditional payment rails, providing smart accounts, automated agents, and programmable card issuance so apps can turn onchain positions into real-world spending. Brahma abstracts infrastructure and settlement for developers, letting them build onchain or hybrid apps without running backend ops.

📋 Description

• Research and develop state-of-the-art voice synthesis models (e.g., TTS, voice cloning, speech-to-speech). • Build and fine-tune models using frameworks like PyTorch and HuggingFace. • Design training pipelines and datasets for scalable voice model training. • Explore techniques for emotional expressiveness, multilingual synthesis, and speaker adaptation. • Work closely with product and creative teams to ensure models meet quality and production constraints. • Stay on top of academic and industrial trends in speech synthesis and related fields.

🎯 Requirements

• Strong background in machine learning and deep learning, with focus on speech/audio. • Hands-on experience with TTS, voice cloning, or related voice synthesis tasks. • Proficiency with Python and PyTorch; experience with libraries like torchaudio, ESPnet, or similar. • Experience training models at scale and working with large audio datasets. • Familiarity with vocoders and transformer-based architectures. • Strong problem-solving skills, ability to work autonomously in a remote-first environment. • PhD degree in Computer Science/ Machine Learning and publications in top venues (Nice to Have). • Contributions to open-source speech research or participation in relevant benchmarks (Nice to Have). • Familiarity with adjacent areas like lip-syncing, audio-driven animation, or expressive speech control (Nice to Have). • Experience with voice datasets or proprietary pipelines (Nice to Have).