Staff Machine Learning Engineer
We are hiring a Staff Machine Learning Engineer to work on translating cutting-edge research into ambitious, customer-centric speech solutions. As innovators in speech technology, our mission is to Understand Every Voice — a vision that has propelled us to be world leaders of Speech AI. Fuelled by innovation, inclusivity, and a passion for making a global impact through world-leading Speech AI, we're looking for an experienced ML Team Lead to accelerate our efforts towards exceptional speech solutions. Our Modelling Team builds and trains a broad spectrum of models, including large self-supervised architectures, advancing Speechmatics’ mission to provide the most accurate speech recognition technology worldwide. It also ensures their deployment into production, working with the latest developments in ML, but also with the best practices for software engineering and model serving. In this role, You will develop and deploy advanced speech systems that power our products, and collaborate with cross-functional teams to deliver scalable, high-performance solutions that deliver business impact. What You’ll Be Doing
- Develop and deploy ML models, translating research into scalable, user-centred solutions
- Optimise ML models for speed, accuracy, and cost efficiency
- Evaluate and integrate cutting-edge approaches into our ML stack
- Collaborate cross-functionally to align initiatives with business goals
- Mentor junior engineers and foster a culture of technical excellence
- Contribute to technical strategy and roadmap to achieve ambitious strategic goals
- Deep understanding of the modern Machine Learning stack, for example:
- Knowledge of contemporary transformer architectures, related concepts (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)
- Proven track record of developing deploying models at scale
- Proficiency in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platforms
- Strong familiarity with software engineering practices and ML testing frameworks
- User-centricity, with understanding how ML solutions address customer needs