Careers / Engineering
Data & Applied ML Engineer
Build the data foundations that analytics and AI features depend on: pipelines, retrieval ingestion, model-ready datasets, and the quality systems that keep them trustworthy.
- Employment
- Full-time (contract to permanent)
- Location
- Remote — North America, Latin America, Europe, or Asia
- Time zone
- At least 4 hours of overlap with U.S. Eastern working hours
Apply for this role
Compensation and benefits are discussed openly with qualified candidates.
The work
What you will do
- Design and operate data pipelines from ingestion through curated, documented models
- Build retrieval ingestion for AI features — chunking, embedding, indexing, and refresh strategies
- Establish data-quality checks, freshness monitoring, and lineage across pipelines
- Create model-ready datasets and APIs product engineers can build on
- Support analytics foundations: semantic layers, reporting models, and governed exports
Requirements
What we need to see
- 4+ years building production data pipelines in Python and SQL
- Orchestration experience (Airflow, Dagster, or similar) and warehouse modeling with dbt
- Practical experience with embeddings and vector search in production
- Strong data-quality instincts — you notice drift before dashboards do
Nice to have
What sets candidates apart
- Production ML workflow experience beyond notebooks
- Healthcare or financial data experience, with the governance sensibilities that come with it
- Streaming or near-real-time pipeline experience