Hours: Full-Time (US EST/Pacific Time overlap required)
Compensation: $8,000 – $11,000 USD
About the Company:
My client is a small, post-Series A AI company building the training data and evaluation infrastructure frontier AI labs use to improve their models, partnering with leading labs to design high-signal datasets and rigorous evaluations beyond static benchmarks. It's a lean, early team where individual contributors have direct, outsized impact on how the next generation of models learns.
Our culture blends the intellectual rigor of top quant shops with the speed and ownership of an early-stage startup experiencing hockey-stick growth.
Role Summary
As our first ML Specialist, you will own our recommendation and ad-serving engine end-to-end. You’ll be responsible for the real-time decision engine that determines which interactive ad reaches which user across massive concurrent traffic.
This is a full-stack ML infrastructure and engineering role (roughly 60–70% focused on systems/infra and 30–40% on modeling). You will build everything from data pipelines and feature stores to production model architecture and low-latency serving infrastructure.
What You Will Build
- Low-Latency Ad Ranking Pipeline: Architect and deploy our multi-stage recommendation pipeline from scratch (Retrieval $rightarrow$ Ranking $rightarrow$ Reranking).
- ML Training & Data Infrastructure: Build scalable data pipelines, feature stores, and automated model training/evaluation loops.
- Context & User Modeling: Extract high-signal embeddings and dynamic context representations from real-time conversational, engagement, and in-game signals.
- Production Serving at Scale: Design sub-second, cost-efficient, high-throughput serving systems capable of processing millions of daily requests with extreme reliability.
Key Requirements
- Experience: 4+ years of hands-on Machine Learning Engineering experience, with at leas
📌 ML Engineer (Medellín)
🏢 Somewhere
📍 Medellín
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