Machine Learning Engineer I

Our engineering group is split into roughly 60 product teams, each owning its services end to end, with on-call shared across time zones. Public sector agencies, utilities and large health systems licence our asset management platform under multi-year contracts.

Position summary:

Briarfield Data is hiring a Machine Learning Engineer I to work remotely from the Netherlands. This hire will help build out our ML platform: feature store, training pipelines, model registry and deployment. Fully remote. You can work from anywhere in the Netherlands. We use Slack, Notion and Google Meet. Cameras on for team calls.

Job duties:

Cut inference cost with quantization, batching and caching. Document model cards, data sources and known failure modes. Set up evaluation harnesses and regression tests for model quality. Monitor models for drift, data quality issues and latency regressions. Build training pipelines in PyTorch or TensorFlow and run them on GPUs in AWS, GCP or Azure.

Minimum qualifications:

1-2 years of software engineering experience, with at least two spent on ML systems in production. Familiarity with Docker, Kubernetes and a cloud ML platform (SageMaker, Vertex AI, Azure ML). Strong Python and solid engineering habits (testing, packaging, code review). Understanding of core ML concepts: overfitting, evaluation metrics, bias in training data. BS or MS in computer science, engineering or a related field. Hands-on experience with PyTorch, TensorFlow or JAX. Knowledge of LLM APIs, prompt design and evaluation methods.

Pay and benefits:

Pension scheme. 25 annual leave days. Training budget. 30% ruling for eligible candidates. Home office allowance.

We look at every application, usually within a week.

Start: Flexible.

Demo job created on 11jobs for testing and demonstrations. It is not an actual opening at Briarfield Data B.V..