Related skills
docker aws python kubernetes gcp📋 Description
- Collaborate with ML Engineers to build ML training pipelines for massive 3D datasets.
- Streamline ML lifecycle from labeling to deployment; reduce tech debt.
- Develop and maintain cloud-native systems and tooling (GCP/Kubernetes) for 3D dental products.
- Write clean, maintainable code and tests to set internal standards.
- Partner with Engineering to influence long-term architectural goals.
🎯 Requirements
- 5+ years in ML or Software Engineering, ideally in a startup.
- Experience building ML platform components: feature stores, model registries, training infra.
- Cloud infra design: Docker, Kubernetes; AWS, GCP, or Azure.
- Large-scale data processing and ML data pipelines.
- Automated build/test/deploy workflows (Buildkite, CI/CD).
- Observability: metrics, logging, tracing for distributed systems.
- Clear communication of complex architectural problems; pragmatic solutions.
- Python ML frameworks (PyTorch, TensorFlow); 3D CV a plus.
🎁 Benefits
- Best-in-class benefits tailored to each country.
- Healthcare, dental, mental health support.
- Parental planning resources and retirement savings options.
- Generous paid time off for all team members.
- Visit Dandy Careers for more information.
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