Machine Learning Engineer

About the Role

real-time ML decision engines

decide, score, suppress, and trigger actions

Key Responsibilities

• Build ML models for classification, scoring, and anomaly detection
• Design

  offline + online

  feature pipelines
• Combine

  rules, heuristics, and ML

  into deterministic systems
• Deploy and monitor ML services in production
• Handle false positives, model drift, and noisy real-world data

Required Skills

• Experience building or working with

  decision, ranking, or scoring systems

• Strong understanding of experimentation and evaluation metrics
• Backend engineering fundamentals (Python / APIs / services)
• Experience deploying models behind Flask or Fast APIs
• Ability to reason about

  negative signals and suppression

• Experience working with sparse, incomplete, or imperfect data

Good to Have

• Feed, content, or recommendation systems experience
• Embedding or NLP-based ranking exposure
• Large-scale experimentation or A/B platforms

What We Value

• Decision quality over model complexity.
• Engineers who

  own outcomes, not notebooks

• Comfort debugging ML behavior in production