We are seeking a Senior MLOps Engineer to join an MVP engagement with a major AAA game publisher, building a test intelligence platform for two game franchises in parallel. A core design principle is full re-derivability and model lineage from day one — every run must be replayable from its stored configuration version and feed read positions. The signal catalog feeds a scoring strategy engine with versioned configurations, and calibration sweeps over historical data produce suggested weight updates surfaced directly in the Settings View.

This role ensures the ML and signal components are production-ready, reproducible, and improvable over time, forming the foundation of the system's long-term value as franchise history accumulates and models are refined.

Responsibilities

• Own Signal Catalogue operations: signal refresh orchestration triggered by feed read-position advances, grain translation between per-test, per-area, and per-run signal families, and provenance capture across all 8 signals
• Operate the Semantic Vector Index versioning:



coordinate with the Senior AI Developer on model and dimension stamp conventions; design and execute the controlled reindex path when the enterprise AI gateway model changes
• Design, implement, and own the Back-test & Calibration Harness: as-of temporal filtering across all record families, replay runner, look-ahead spot audit, and configuration sweep runner
• Enforce holdout patch-set discipline, configuration sweep over route limits, thresholds, weights, and Composition setting; produce catch-rate vs. scope tables per candidate configuration and publish winning configurations as suggested-weight proposals into the Settings View
• Lead Model Generation & Experimentation: systematic experimentation framework over scoring strategy configurations, tracking which signal weights and route combinations yield the best catch-rate vs. scope trade-off
• Maintain model lineage across configuration versions for both franchises
• Implemen

📌 Senior MLOps Engineer (Argentina)
🏢 EPAM Systems
📍 Argentina