A tiny, well-funded team mapping the hidden patterns in how ideas, tastes, and behaviors spread across populations.
Senior Data & Machine Learning Engineer
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We’re building systems that ingest enormous, noisy streams of behavioral and semantic data and turn them into structured models of cultural change — what people care about, how that shifts, and why. This role sits at the intersection of data engineering and applied machine learning, where you’ll design pipelines that collapse raw signal into queryable, vector-native representations and then build the retrieval and reasoning layers that make those representations useful to Fortune 500 marketing and strategy teams. You’ll work primarily in PostgreSQL and vector databases, wrestling with entity resolution, temporal embeddings, and recursive clustering problems that resist off-the-shelf solutions. The output isn’t a dashboard — it’s a living model of collective attention, and you’ll own the infrastructure that keeps it accurate, fresh, and fast.
What they're looking for
- Deep fluency in PostgreSQL, including advanced indexing, query optimization, and working with semi-structured data at scale.
- Hands-on experience building production systems on vector databases (Pinecone, Weaviate, Milvus, or similar) for semantic search or recommendation use cases.
- 5+ years of professional experience spanning data engineering and machine learning, with a strong grasp of embedding techniques, clustering, and information retrieval.
- Comfort working in a small, high-autonomy team where you define your own roadmap and ship end-to-end — from data ingestion to model evaluation.
- Clear communication habits and a instinct for reducing ambiguous, real-world phenomena to tractable technical problems.