Machine Learning Engineer - West London (6 Months)

microTECH Global Limited; City of London; On-site; GBP 65,000 - 85,000; Full time

Job summary

A leading technology firm in the United Kingdom is seeking a Senior Machine Learning Research Engineer to drive research and development for innovative AI algorithms, with a focus on audio and speech processing. Candidates should hold an MSc or PhD in a related field and have strong experience in machine learning, deep learning, and audio processing. This permanent role emphasizes collaboration within a multi-disciplinary team and offers opportunities to tackle complex technical challenges.

Qualifications

• MSc or PhD in Artificial Intelligence, Computer Science, or related discipline is required.
• Strong experience in audio/speech processing techniques.
• Proficient in machine learning and deep learning frameworks.

Responsibilities

• Drive research and development of AI algorithms for audio/speech processing.
• Deliver significant components of complex research projects.
• Collaborate with a multi-disciplinary team to guide technical developments.

Skills

Machine learning fundamentals

Deep learning techniques

Audio/speech processing

Python programming

Communication skills

Collaboration

Problem-solving skills

Education

MSc/PhD in AI or related fields

Tools

TensorFlow

PyTorch

Git

Job description

This role is available on a permanent basis but we are also open to hiring a contractor for an initial 6 month period, working via agency. The role is inside IR35.

Role and Responsibilities

As a Senior Machine Learning Research Engineer in Speech/Audio/Gen-AI, you will:

• 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 degree 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 areas such as 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.

Desirable Skills

• Experience with in 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).