Applied ML Engineer

Role: Applied ML Engineer Location: Remote Duration: 10+ Months Only W2Primary Skill Required for the Role: Node.JS Level Required for Primary Skill: Advanced (6-9 years experience)Additional Skills Requested for Role Python AI: Advanced (6-9 years experience) Required MACHINE LEARNING: Advanced (6-9 years experience): Required Kafka Intermediate (3-5 years experience) Preferred Pytorch Intermediate (3-5 years experience) Required Machine Learning Operations (MLOps) Advanced (6-9 years experience) Required Job Qualification: Need Applied 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.

Created: 2026-03-04