ML Data & Platform Engineer
Speechmatics· Machine Learning
Hybrid (London)Full-timePosted 1mo ago
About the role
Own the infrastructure powering speech AI models: data pipelines for training data and the platform for training, evaluating, and serving models in production. Cross-functional role spanning data infrastructure, distributed systems, and production ML, focused on end-to-end ownership and rapid production readiness.
Responsibilities
- Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models
- Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale
- Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production
- Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency
- Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to catch issues early and keep things running smoothly
- Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference
- Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale
Qualifications
- Strong proficiency in Python and SQL, with a solid backend or data engineering foundation
- Hands-on experience with containerisation and orchestration (Docker, Kubernetes), and working with a major cloud provider
- Experience building data pipelines and ETL/ELT processes at scale, including web scraping or automated data collection
- A solid understanding of the ML lifecycle, from data through to model training, evaluation, and serving
- Experience with data quality practices (validation, cleaning, normalisation) and/or production-grade observability
- Ability to design resilient, scalable architectures, and comfort operating and troubleshooting distributed systems
- MLOps experience, for example model serving, experiment tracking, GPU/distributed training optimisation, or reproducible ML workflows
- A self-starter mentality: comfortable identifying problems and driving fixes without needing detailed direction
Skills
Required:PythonSQLDockerKubernetesCloud (major provider)Data pipelines / ETLWeb scrapingMLOps
Benefits
- Private Medical, and Dental for you and your family
- global working opportunities
- generous holiday allowance and pension/401K matching
- working from home allowance for tech or home office equipment
- choice of laptop and accessories
- parental leave support including adoption assistance and reproductive health services
Last updated Sep 10, 2026. Interested? Apply on the company site.
About Speechmatics
Speechmatics offer the most accurate AI speech technology for enterprise - with AI transcription, real-time translation and text-to-speech components. Try our Speech API today!
AI speech technologyAI voiceCase studiesLow-latency speech-to-textMultilingualReal-time transcriptionSpeech APIsSpeech APIs powering Voice AI
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