ML Data & Platform Engineer: Pipelines, MLOps & Production

Speechmatics; Cambridge (MA); Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Private Medical

Dental for you and family

Pension/401K matching

Home office allowance

Global opportunities

Flexible working

Office days 2-3 per week

Job summary

Speechmatics seeks an ML Data & Platform Engineer to own the infrastructure powering our speech AI models. You’ll manage pipelines, data acquisition, and the platform that trains, evaluates, and serves models in production.

Join a cross-functional ML team and own problems end-to-end, improving data quality and deployment speed while ensuring reliability and observability across distributed systems.

Qualifications

• Strong Python and SQL skills with backend/data engineering foundation.
• Hands-on experience with containerisation/orchestration (Docker, Kubernetes) and a major cloud provider.
• Experience building data pipelines and ETL/ELT at scale, including web scraping or automated data collection.
• Solid understanding of the ML lifecycle from data to model training, evaluation, and serving.
• Experience with data quality practices and observability in production.
• Ability to design resilient, scalable architectures and operate distributed systems.
• MLOps experience (model serving, experiment tracking, GPU/distributed training).
• Self-starter who can identify problems and drive fixes without detailed direction.

Responsibilities

• Design, build, and maintain scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train models.
• Develop and maintain web scraping/data acquisition solutions to keep training data fresh and high quality at scale.
• Build and operate infrastructure that lets the ML team deploy and evaluate models quickly and serves models reliably in production.
• Optimise infrastructure for iteration speed and production reliability including GPU utilisation, job scheduling, and training efficiency.
• Implement observability across data pipelines and ML systems to catch issues early and keep systems running smoothly.
• Troubleshoot complex issues across distributed systems spanning data, training, and inference.
• Continuously improve data and MLOps practices and help shape platform roadmap as we scale.

Skills

Python

SQL

Docker

Kubernetes

Cloud

ETL/ELT

ML lifecycle

Observability

Distributed systems

MLOps

Self-starter

Tools

Docker

Kubernetes

Cloud platforms

Job description

Speechmatics seeks an ML Data & Platform Engineer to own the infrastructure powering our speech AI models. You’ll manage pipelines, data acquisition, and the platform that trains, evaluates, and serves models in production.

Join a cross-functional ML team and own problems end-to-end, improving data quality and deployment speed while ensuring reliability and observability across distributed systems.