Senior Applied ML Engineer
Core
Evaluate and productionise existing ML models to deliver metadata enrichment for data licensing opportunities supporting frontier AI labs.
Role type
Senior Applied ML Engineer (production inference)
Builds
Production ML inference components and metadata enrichment workflows
Domain
AI/ML, Data Licensing, Cloud Infrastructure
Deliverable
production ML models
Required skills
Python software engineering, ML model evaluation, PyTorch/TensorFlow/scikit-learn/Hugging Face, scalable ML inference systems, distributed cross-cloud workflows, model optimization
Preferred skills
MLflow, SageMaker/Vertex AI/Databricks, image/video/audio model evaluation, Snowflake/DBT/Clickhouse
Responsibilities
Implement and evolve model-evaluation and productionisation standards; independently own assigned enrichment workflows from evaluation through production delivery; evaluate candidate models using quality measures and threshold analysis; develop tested Python inference components; support ad-hoc metadata backfills by validating outputs and estimating costs; move enrichment components to corpus-scale execution; assess model licensing and data-handling constraints
Seniority
Senior, hands-on IC
