Principal Machine Learning Engineer
Role details
Job location
Tech stack
Job description
We are hiring a Principal Machine Learning Engineer to work on cutting-edge Research & Development. As innovators in speech technology, our mission is to Understand Every Voice-a vision that has propelled us to be world leaders of Voice AI, with STT, TTS, and Flow; our brand new Conversational AI platform. Fuelled by innovation, inclusivity, and a passion for making a global impact through world-leading Speech AI, we're looking for an experienced Machine Learning Engineer to accelerate our efforts towards exceptional speech solutions.
Our Modelling Team trains diverse models, including large self-supervised ones, supporting Speechmatics towards being the most accurate speech recognition system globally. It also ensures their deployment into production, working with the latest developments in ML, but also with the best engineering practices for software engineering and model serving.
What you'll be doing:
- Drive diverse groups of engineers to achieve ambitious goals; you will work on complex R&D projects, and guide others by defining research milestones and collaborating together.
- Raise the bar for machine learning at Speechmatics, by applying your innovative ideas and experiences to improve the efficiency, effectiveness, and best practices across all of our machine learning teams.
- Set a forward-thinking vision for Speechmatics' business as a world leader in Voice AI; with your passion and understanding of the latest machine learning developments, you will influence our product and technical direction.
- Grow the engineers around you through mentorship and support, ensuring we are all continuously improving together.
This position allows you to influence what the ML team is working towards, and to efficiently leverage other engineers to increase the output of your experience.
Requirements
- Someone who can act as a tech lead and use their experience to be not only an example for their coworkers, but also a guardrail.
- Demonstrated experience in collaboratively pursuing ambitiousR&D agendas.
- Balances attention to detail with a view on the big-picture, long-term company vision, and is able to relate company goals to the goals of the team members they work with.
- Deep understanding of the modern Machine Learning stack, for example:
- Knowledge of contemporary transformer architectures (e.g., GQA, KV-caching) and best practices.
- Expertise in distributed training techniques.
- Familiarity with optimisation strategies for model inference (e.g., dynamic batching, flash attention, speculative decoding).
- With preferred backgrounds covering some of the following:
- Publications in top-tier conferences.
- Contributions to popular open-source repositories.
- Exceptional technical writing skills as evidenced by relevant publications or blogs.