Lead Machine Learning Engineer

Intellectual Capital Resources; Greater London; On-site; GBP 59,000 - 99,000; Full time

Job summary

Intellectual Capital Resources is seeking a Machine Learning Research Lead to guide strategy and hands-on development across audio ML domains. You will lead a small team of researchers and engineers, shaping the roadmap for next‑generation audio technologies used by thousands of users worldwide.

Based in the United Kingdom, the role requires experience leading ML research or engineering teams, strong Python skills and hands-on PyTorch; you will translate research into production‑ready systems

Qualifications

• MSc or PhD in AI, ML, CS/Engineering, Mathematics, or related field.
• 3+ years leading ML research or engineering teams.
• Strong Python skills and deep expertise with PyTorch.
• Experience applying and optimizing AI/ML algorithms in production.
• Knowledge of real-time audio signal processing or real-time ML.
• Experience in audio super-resolution, speech enhancement and/or speech-to-text.
• Strong communication skills to convey complex research outcomes.
• Background or interest in music or signal processing.

Responsibilities

• Refine and execute our research strategy and long‑term roadmap for audio machine learning.
• Identify emerging opportunities in deep learning for audio and evaluate their applicability to future products.
• Lead multiple concurrent research streams, including audio super‑resolution, speech enhancement and speech‑to‑text.
• Work closely with product and engineering teams to transition research models into scalable, production‑ready systems.
• Present research outcomes to stakeholders across engineering, product, commercial and leadership teams.
• Foster a collaborative, open and product‑focused research environment.

Skills

Communication

Real-time ML

Audio processing

Education

MSc/PhD in AI/ML/CS/Math

Tools

PyTorch

Python

Job description

Salary: £59,000 - 99,000 per year

Requirements

• MSc or PhD in Artificial Intelligence, Machine Learning, Computer Science/Engineering, Mathematics, or a related field
• 3+ years of experience leading machine learning research or engineering teams
• Strong Python skills and deep expertise with at least one modern ML framework such as PyTorch
• Proven experience applying and optimizing AI/ML algorithms in a production-oriented environment
• Knowledge of real-time audio signal processing or real-time ML
• Experience in audio super-resolution, speech enhancement and/or speech-to-text
• Strong communication skills, with the ability to convey complex research outcomes to diverse audiences
• Background or interest in music or signal processing

Responsibilities

• Refine and execute our research strategy and long‑term roadmap for audio machine learning
• Identify emerging opportunities in deep learning for audio and evaluate their applicability to future products
• Lead multiple concurrent research streams, including audio super‑resolution, speech enhancement and speech‑to‑text
• Work closely with product and engineering teams to transition research models into scalable, production‑ready systems
• Present research outcomes to stakeholders across engineering, product, commercial and leadership teams
• Foster a collaborative, open and product‑focused research environment

Technologies

• AI
• Machine Learning
• PyTorch
• Python
• Computer Vision

More

We are partnered with a cutting‑edge audio AI company developing next‑generation technology to improve the quality, clarity and intelligence of digital sound. Our products apply advanced machine learning and signal processing to deliver high‑fidelity voice isolation, audio enhancement and new listening experiences across consumer, enterprise and professional markets. We are looking for a Machine Learning Research Lead to guide strategy, research direction and hands‑on development across multiple audio ML domains. You will lead a small, high‑performing team of researchers and engineers, shaping the roadmap for new audio technologies used by thousands of people worldwide.