ML Data & Platform Engineer
Salary not listed • Cambridge, England, United Kingdom • Full-time
Posted 1mo ago
Job Location
Cambridge, England, United Kingdom
Also open in London, England, United Kingdom
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
We are seeking an ML Data & Platform Engineer to manage the infrastructure supporting our speech AI models. This includes the pipelines for data sourcing and preparation, as well as the platform for training, evaluating, and serving models in production. This broad, cross-functional role is ideal for someone who thrives on end-to-end problem ownership across data infrastructure, distributed systems, and production ML, aiming to accelerate the delivery of better models.
Responsibilities
- Design, build, and maintain scalable data pipelines for ingesting, transforming, validating, and storing large datasets.
- Develop and maintain web scraping and data acquisition solutions for training datasets.
- Build and operate infrastructure for rapid model deployment, evaluation, and efficient production serving.
- Optimize infrastructure for iteration speed and production reliability, including GPU utilization and job scheduling.
- Implement observability (monitoring, logging, alerting) for data pipelines and ML systems.
- Troubleshoot complex issues across distributed systems, including data infrastructure, training, and inference.
- Continuously improve data and MLOps practices and contribute to platform evolution.
Requirements
- Strong proficiency in Python and SQL with a backend or data engineering foundation.
- Hands-on experience with containerization and orchestration (Docker, Kubernetes).
- Experience working with a major cloud provider.
- Experience building data pipelines and ETL/ELT processes at scale, including web scraping.
- Solid understanding of the ML lifecycle (data, training, evaluation, serving).
- Experience with data quality practices and/or production-grade observability.
- Ability to design resilient, scalable architectures and troubleshoot distributed systems.
- MLOps experience (e.g., model serving, experiment tracking, distributed training).
- Self-starter mentality, comfortable identifying and driving solutions independently.
Benefits
- Paid internships and first-job opportunities
- Training and development support
- Incredibly flexible working
- Regular company lunches
- Birthday celebrations
- Private Medical and Dental for you and your family
- Global working opportunities
- Generous holiday allowance
- Pension/401K matching
- Working from home allowance for tech or home office equipment
- Choice of laptop and accessories
- Parental leave support (including adoption assistance and reproductive health services)