ML Data & Platform Engineer

📋 Description

• Designing, building, and maintaining scalable data pipelines for ingesting, transforming
• Developing and maintaining web scraping and data acquisition solutions to keep training datasets
• Building and operating the infrastructure that lets the ML team deploy and evaluate new models
• Optimising infrastructure for both iteration speed and production reliability, including GPU
• Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to
• Troubleshooting complex issues across distributed systems, spanning data infrastructure, training

🎯 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
• Experience building data pipelines and ETL/ELT processes at scale, including web scraping or
• A solid understanding of the ML lifecycle, from data through to model training, evaluation, and
• Experience with data quality practices (validation, cleaning, normalisation) and/or
• Ability to design resilient, scalable architectures, and comfort operating and troubleshooting

🎁 Benefits

• Incredibly flexible working
• Regular company lunches
• Birthday celebrations
• Private Medical and Dental for you and your family
• Global working opportunities
• Generous holiday allowance