ML Data & Platform Engineer: Scale Pipelines & MLOps

Speechmatics; United Kingdom; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Private Medical

Dental for family

Global opportunities

Holiday allowance

Pension matching

Home office allowance

Parental leave support

Job summary

Speechmatics is seeking an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models—pipelines for sourcing training data and a platform that trains, evaluates, and serves models in production.

This broad, cross-functional role covers data infrastructure, distributed systems, and production ML, with end-to-end ownership of problems to speed up model delivery.

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.

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

Skills

Python

SQL

Distributed systems

MLOps experience

Data pipelines

Problem solving

Tools

Docker

Kubernetes

AWS/GCP/Azure

Job description

Speechmatics is seeking an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models—pipelines for sourcing training data and a platform that trains, evaluates, and serves models in production.

This broad, cross-functional role covers data infrastructure, distributed systems, and production ML, with end-to-end ownership of problems to speed up model delivery.