ML Data & Platform Engineer

Highlights

• Own infrastructure powering speech AI models from data to production serving.
• Tackle speech AI's unique data challenge at the centre of better models.
• Remove friction across ML lifecycle to ship better models faster.

What they offer

• Private Medical and Dental coverage for you and your family
• Generous holiday allowance
• Pension/401K matching
• Global working opportunities
• Work from home allowance for tech or home office equipment
• Choice of laptop and accessories
• Parental leave support including adoption and reproductive health services

Ideal candidate

A self-starting engineer who loves owning end-to-end problems across data and ML systems and thrives in cross-functional work to get better models to production faster.

Requirements

• 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