Senior Machine Learning Engineer
I am working with an established R&D group who are expanding their AI research team and seeking a Senior Machine Learning Research Engineer with strong expertise in speech, audio, and generative AI. This is an opportunity to contribute to cutting-edge research that will be deployed across large-scale consumer products, working end-to-end from concept development through to production. The team is building next-generation machine learning systems for audio understanding, speech processing, and on-device intelligence. You will work on high-impact research projects while collaborating closely with experienced ML engineers and scientists. The role As a Senior ML Research Engineer, You Will
- Research, design, and develop novel algorithms for speech, audio and generative AI
- Build and optimise ML models for real-world deployment, including mobile or embedded environments
- Lead technically significant components of complex research projects.
- Deliver clean, well-structured and well-documented code following modern software engineering practices
- Work closely with cross-functional teams, providing technical leadership and guidance when required
- Identify challenges proactively and drive solutions from prototype through to production
- Contribute to internal tooling, infrastructure, and scalable training/evaluation pipelines
- MSc or PhD in Computer Science, Machine Learning, Signal Processing, Engineering, Mathematics, or similar
- Strong professional experience in Python for ML development (C++/Java/Kotlin beneficial but not essential)
- Deep understanding of machine learning and deep learning fundamentals (architectures, optimisation, evaluation)
- Solid track record in speech/audio processing, e.g. ASR, TTS, speech enhancement, audio analysis, NLP-audio interfaces, etc
- Experience with PyTorch or TensorFlow
- Strong engineering fundamentals: Git, CI/CD, testing, code quality, agile workflows
- Ability to take research concepts through to production-ready implementations
- Strong communication and collaboration skills
- Experience with Generative AI applied to audio or speech (diffusion, autoregressive models, speech synthesis, voice conversion etc.)
- Publications in relevant ML/AI/Signal Processing conferences or journals
- Experience with open-source toolkits such as SpeechBrain, ESPnet, Hugging Face, NeMo, Kaldi
- Experience deploying ML models to mobile platforms
- Knowledge of large-scale or distributed training pipelines
- Experience with cloud platforms (AWS, GCP or Azure)