Machine Learning Engineer

ML Engineer to design, deploy, and operationalize machine-learning models that power
the Decision Engine, enabling intelligent selection of the most relevant decision using
real-time and historical data. This role focuses on building and integrating Python-based ML
models (e.g., propensity, ranking, uplift, or optimization models), serving models via low-latency APIs,
and integrating with feature stores, streaming pipelines (Kafka or equivalent), and decisioning
services built in Node.js and/or Python. The ideal candidate has strong experience with ML
frameworks (e.g., TensorFlow, PyTorch, scikit-learn), MLOps practices (model versioning, monitoring,
retraining), and understands explainability, bias, and guardrails in regulated environments. The
engineer will collaborate closely with data engineers, rules engineers, and backend teams to ensure
models are reliable, observable, and safely embedded into production decision workflows at scale."