ML Data & Platform Engineer

Salary: £58,000 - 84,000 per year

Requirements:

• We need strong proficiency in Python and SQL, with a solid backend or data engineering foundation.
• We need hands-on experience with containerisation and orchestration, including Docker and Kubernetes, and experience working with a major cloud provider.
• We need experience building data pipelines and ETL/ELT processes at scale, including web scraping or automated data collection.
• We need a solid understanding of the ML lifecycle, from data through to model training, evaluation, and serving.
• We need experience with data quality practices such as validation, cleaning, and normalisation, and/or production-grade observability.
• We need the ability to design resilient, scalable architectures and comfort operating and troubleshooting distributed systems.
• We need MLOps experience, such as model serving, experiment tracking, GPU/distributed training optimisation, or reproducible ML workflows.
• We need a self-starter mentality and comfort identifying problems and driving fixes without detailed direction.

Responsibilities:

• We design, build, and maintain scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models.
• We develop and maintain web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale.
• We build and operate the infrastructure that lets our ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production.
• We optimise infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency.
• We implement observability across data pipelines and ML systems, including monitoring, logging, and alerting, to catch issues early and keep things running smoothly.
• We troubleshoot complex issues across distributed systems spanning data infrastructure, training, and inference.
• We continuously improve our data and MLOps practices and help shape the roadmap for how our platform evolves as we scale.

Technologies:

• AI
• Backend
• Cloud
• Docker
• ETL
• Support
• Kubernetes
• Machine Learning
• MLOps
• Model Serving
• Model Training
• Python
• SQL
• Web

More:

We are Speechmatics, the leading expert in Speech Intelligence, using AI and Machine Learning to unlock business value in human speech worldwide. We work with a diverse mix of global companies, and our technology integrates into customer stacks across industries and use cases. You will join a cross-functional ML team working across the full stack, with Focus Fridays for uninterrupted focus and Together Tuesdays for team meetings. We offer a hybrid working model with 2-3 designated office days each week, plus flexible working, regular company lunches, birthday celebrations, training and development support, private medical and dental cover for you and your family, global working opportunities, generous holiday allowance, pension/401K matching, a home office or tech allowance, and support for parental leave and family-related services. We welcome different experiences, viewpoints, and identities and aim to build an inclusive workplace where every voice is respected and valued.

last updated 36 week of 2026