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python machine learning monitoring experimentation feature store📋 Description
- End-to-end ML ownership: feature design, model training, deployment, monitoring.
- Collaborate with data engineers, platform engineers, and product teams.
- Design & deploy production models for risk, fraud, trust & safety, compliance.
- Monitor models in production; detect drift and retrain.
- Drive online experiments and offline evaluation to prove impact.
- Contribute to feature store, model management, and pipelines to scale ML.
🎯 Requirements
- 7+ years applied ML experience in risk, fraud, fintech.
- End-to-end ML ownership from research to deployment.
- Strong Python and ML frameworks; production-grade code.
- Experience with ML infra: feature stores, model management, pipelines, monitoring.
- Senior IC; set technical direction and mentor peers.
- Cross-functional collaboration with data/platform engineers and product teams.
- Expertise in classification challenges: imbalanced labels, sparse signals, cold start.
- Nice to have: B2B SaaS ML for enterprise; graph/LLM feature generation.
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