ML Data Platform Engineer — Scale Data & Models

Speechmatics; London (KY); Hybrid; USD 110,000 - 170,000; Full time

Benefits offered by this job

Private Medical and Dental for you and

Global working opportunities

Generous holiday allowance

Pension/401K matching

Home office equipment allowance

Parental leave support

Job summary

Speechmatics seeks an ML Data & Platform Engineer to own infrastructure powering speech AI models, including data pipelines, data acquisition, and production ML. You’ll work across data infra, distributed systems, and production ML, owning problems end to end.

You’ll join a hybrid team with 2-3 in-office days weekly, focusing on scalable pipelines and observability to accelerate model deployment.

Qualifications

• Proficiency in Python and SQL with backend/data engineering foundation.
• Hands-on experience with Docker, Kubernetes, and a major cloud provider.
• Experience building scalable ETL/ELT data pipelines at scale, including data collection.
• Solid understanding of the ML lifecycle from data to model serving.
• Experience with data quality, validation, cleaning, and observability.
• Ability to design resilient, scalable distributed architectures.
• ML Ops experience (model serving, experiment tracking, GPU training).
• Self-driven with initiative to identify problems and fix them.

Responsibilities

• Design, build, and maintain scalable data pipelines for ingesting, transforming, validating, and storing data.
• Develop web scraping/data acquisition solutions to keep training datasets fresh at scale.
• Build and operate infrastructure for deploying/evaluating models in production.
• Optimize infrastructure for iteration speed and production reliability, including GPU usage and scheduling.
• Implement observability across data pipelines and ML systems to catch issues early.
• Troubleshoot complex issues across distributed systems spanning data, training, and inference.
• Contribute to roadmap for data and MLOps platform evolution as we scale.

Skills

Python

SQL

Distributed systems

Data engineering

MLOps

Observability

Self-starter

Tools

Docker

Kubernetes

Cloud provider (AWS/GCP/Azure)

Job description

Speechmatics seeks an ML Data & Platform Engineer to own infrastructure powering speech AI models, including data pipelines, data acquisition, and production ML. You’ll work across data infra, distributed systems, and production ML, owning problems end to end.

You’ll join a hybrid team with 2-3 in-office days weekly, focusing on scalable pipelines and observability to accelerate model deployment.