Principal Machine Learning Engineer

Stack

Responsibilities

• ▹Developing and deploying ML models, translating research into scalable, maintainable code and services
• ▹Optimizing ML models for speed, accuracy and cost efficiency
• ▹Evaluating and integrating cutting-edge approaches into the ML stack
• ▹Identifying and solving complex ML problems across the organization
• ▹Defining and enforcing best practices for code quality and model lifecycle management
• ▹Mentoring engineers and fostering a culture of technical excellence and innovation
• ▹Co-defining the long-term technical vision

Requirements

• ▹Deep understanding of the modern ML stack, e.g. contemporary transformer architectures (GQA, KV-caching)
• ▹Expertise in distributed training techniques
• ▹Familiarity with model inference optimization strategies (dynamic batching, flash attention, speculative decoding)
• ▹Proven track record of developing and deploying models at scale
• ▹Expertise in Python, ML frameworks (TensorFlow, PyTorch) and cloud platforms
• ▹Strong familiarity with MLOps principles, CI/CD pipelines and containerization (Docker, Kubernetes)

Nice to have

• ▹Experience with speech-to-text or text-to-speech
• ▹Contributions to open-source projects or published research at top-tier conferences

Soft skills

What we offer

• ▹Focus Fridays: an undisturbed day of focus each week
• ▹Together Tuesdays: team meetings
• ▹Hybrid arrangement with 2-3 office days per week

About the company

Speechmatics is the leading expert in Speech Intelligence, using AI and Machine Learning to unlock business value in human speech worldwide, striving to build the most accurate speech recognition system globally.