Machine Learning - (Speech) - Contract

Senior Machine Learning Research Engineer - Speech, Audio, and Generative AI

This role is available on a permanent basis or as a 6-month contractor via an agency. The role is inside IR35.

Role and Responsibilities

• Drive the research, design, development, and evaluation of innovative AI algorithms and models, with a primary focus on audio and speech processing.
• Lead the development of robust and scalable software solutions for deployment on flagship mobile devices.
• Independently own and deliver significant components of complex research projects, from initial concept to production readiness.
• Design, implement, and maintain high-quality, well-documented code, adhering to best software development practices.
• Collaborate closely with a multi-disciplinary team of researchers and engineers, providing technical guidance and mentorship.
• Proactively identify and address technical challenges, proposing creative solutions and ensuring the successful delivery of projects.
• Contribute to the development of internal tools and infrastructure to support research and development efforts.

Skills and Qualifications

Required Skills

• MSc/PhD in Artificial Intelligence, Computer Science/Engineering, Electrical Engineering, Mathematics, or a related discipline.
• Professional software development experience with Python (experience with C++, Java, or Kotlin is a plus).
• Deep understanding of machine learning and deep learning fundamentals, including various architectures, training techniques, and evaluation metrics.
• Strong experience in audio/speech processing, including speech recognition, speech enhancement, audio analysis, text-to-speech synthesis, and natural language processing.
• Proficiency with machine learning frameworks such as TensorFlow or PyTorch.
• Solid understanding of software engineering principles, including version control (Git), CI/CD pipelines, and agile development methodologies.
• Excellent communication, collaboration, and problem-solving skills.
• Demonstrated ability to translate research ideas into practical, production-ready solutions.
• Experience with generative AI, particularly in the context of audio/speech technologies.
• A strong publication record in top-tier machine learning, artificial intelligence, or signal processing conferences and journals (e.g., ICML, NeurIPS, ICLR, CVPR, SysML, INTERSPEECH, ICASSP, IEEE/ACM TASLP, IEEE TPAMI, JMLR).
• Experience with open-source speech processing toolkits (e.g., Hugging Face Transformers, SpeechBrain, ESPnet, Kaldi, NeMo).
• Experience developing and deploying AI models on Android mobile platforms.
• Proven experience in building and maintaining large-scale, distributed training pipelines.
• Experience with cloud computing platforms (e.g., AWS, Azure, GCP).

Seniority Level

• Associate

Employment Type

• Contract

Job Function

• Software Development

Location: London, England, United Kingdom

Salary: $150,000 - $200,000 per annum

• MSc/PhD in Artificial Intelligence, Computer Science/Engineering, Electrical Engineering, Mathematics, or a related discipline.
• Professional software development experience with Python (experience with C++, Java, or Kotlin is a plus).
• Deep understanding of machine learning and deep learning fundamentals, including various architectures, training techniques, and evaluation metrics.
• Strong experience in audio/speech processing, including speech recognition, speech enhancement, audio analysis, text-to-speech synthesis, and natural language processing.
• Proficiency with machine learning frameworks such as TensorFlow or PyTorch.
• Solid understanding of software engineering principles, including version control (Git), CI/CD pipelines, and agile development methodologies.
• Excellent communication, collaboration, and problem-solving skills.
• Demonstrated ability to translate research ideas into practical, production-ready solutions.
• Experience with generative AI, particularly in the context of audio/speech technologies.
• A strong publication record in top-tier machine learning, artificial intelligence, or signal processing conferences and journals (e.g., ICML, NeurIPS, ICLR, CVPR, SysML, INTERSPEECH, ICASSP, IEEE/ACM TASLP, IEEE TPAMI, JMLR).
• Experience with open-source speech processing toolkits (e.g., Hugging Face Transformers, SpeechBrain, ESPnet, Kaldi, NeMo).
• Experience developing and deploying AI models on Android mobile platforms.
• Proven experience in building and maintaining large-scale, distributed training pipelines.
• Experience with cloud computing platforms (e.g., AWS, Azure, GCP).