Principal Machine Learning Engineer at global leader in Voice AI

Principal Machine Learning Engineer

Salary

Not Disclosed

Company Description

Global leader in Voice AI and speech recognition technology headquartered in London

Job Description

You will lead the translation of cutting-edge research into scalable, customer-centric speech solutions. This high-ownership role involves developing diverse ML models, including large self-supervised architectures, to maintain the world’s most accurate speech recognition system. You will span the entire codebase, driving technical vision and mentoring engineering teams to achieve excellence in model deployment.

Location

London, UK

Why this role is remarkable

• Work at the forefront of Voice AI innovation, building models that help the world “Understand Every Voice” through world-leading speech technology.
• Take on a high-impact technical leadership role with total ownership, co-defining the long-term technical vision for an organization at the peak of its market.
• Join a specialized modeling team that balances high-level research with robust engineering practices, utilizing the latest in transformer architectures and MLOps.

What You Will Do

• Develop and optimize advanced ML models for speed, accuracy, and cost efficiency, ensuring seamless transition from research to production.
• Define and enforce technical best practices across the organization for code quality, model lifecycle management, and containerized deployment.
• Mentor fellow engineers and foster a culture of technical excellence while identifying and solving complex ML bottlenecks across the entire product stack.

The ideal candidate

• Possesses deep expertise in the modern ML stack, including contemporary transformer architectures (GQA, KV-caching) and distributed training techniques.
• Demonstrates a proven track record of deploying large-scale models using Python, PyTorch/TensorFlow, and MLOps tools like Docker and Kubernetes.
• Brings a specialized background in speech-to-text or text-to-speech technology, ideally with contributions to open-source projects or top-tier research publications.

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