Principal Machine Learning Engineer (AI)

TL;DR

Principal Machine Learning Engineer (AI): Building and deploying advanced speech recognition models at scale with an accent on model optimization, production lifecycle management, and architectural leadership. Focus on translating cutting-edge research into performant, maintainable services while driving technical vision and mentoring engineering teams.

Location: Cambridge, United Kingdom (Hybrid: 2-3 days in office required)

Company

hirify.global is a leading expert in Speech Intelligence, utilizing AI and Machine Learning to unlock value in human speech globally through scalable, accurate speech recognition technology.

What you will do

• Develop and deploy advanced ML models, ensuring they translate effectively into scalable production code.
• Optimize models for speed, accuracy, and cost-efficiency to enhance overall system performance.
• Integrate cutting-edge AI approaches into the existing ML stack and infrastructure.
• Define and enforce best practices for code quality, model lifecycle management, and CI/CD pipelines.
• Mentor engineers and cultivate a culture of technical excellence and innovation.
• Collaborate to co-define the long-term technical vision for ML initiatives.

Requirements

• Deep understanding of the modern ML stack, including contemporary transformer architectures and distributed training.
• Proven track record of deploying ML models at scale.
• Expertise in Python, ML frameworks (TensorFlow or PyTorch), and cloud platforms.
• Strong familiarity with MLOps principles, containerization (Docker, Kubernetes), and CI/CD pipelines.
• Must be able to work in a hybrid capacity in Cambridge, UK.

Nice to have

• Experience with speech-to-text or text-to-speech technologies.
• Contributions to open-source projects.
• Published research in top-tier conferences.

Culture & Benefits

• Flexible working environment with a focus on work-life balance.
• Comprehensive health benefits including private medical and dental coverage.
• Generous holiday allowance and pension matching.
• Learning and development support for career progression.
• Structured hybrid work policy designed to foster team synergy.
• Support for parents including parental leave and adoption assistance.