Responsibilities
- Hands-on develop, productionize, and operate Machine Learning models and pipelines to improve a diverse range of Plaid products.
- Continuously proposing and developing new features to improve the AI/ML model performance.
- Working with the ML infrastructure team to improve ML infrastructure that powers the end-to-end ML development lifecycle.
- Debugging ML production issues and ensuring stable model serving.
- Work collaboratively with cross-functional partners to identify opportunities for business impact, understand, refine, and prioritize requirements for AI/ML models, drive engineering decisions, and quantify impact.
Qualifications
- 8+ years of experience developing, training, and deploying ML models in production environments
- Proven experience building and maintaining data-intensive backend applications within large, distributed systems
- Strong programming skills in Python and familiarity with tools such as Spark, Jupyter, and standard ML libraries
- Background in fintech or other data-rich, regulated domains
- Demonstrated ability to take ownership and drive projects from concept to measurable business impact
- Solid understanding of data engineering and analytics concepts
- Skilled at collaborating across technical and non-technical teams
- Master’s degree (or equivalent experience) in Computer Science, Mathematics, Engineering, or a related field
- Nice to Have: Hands-on experience with data engineering or analytics tooling
- Nice to Have: Experience applying NLP techniques in production systems
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Engineering Manager - Machine Learning
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Engineering Manager - Update Pipeline
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Senior Software Engineer - Backend
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Senior Software Engineer - Credit ML Products
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Senior Software Engineer - Data Infrastructure
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Senior Software Engineer - Fullstack
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Senior Software Engineer - ML Infrastructure
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Software Engineer - Backend
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Software Engineer - Platform
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Staff Machine Learning Engineer - Fraud Data
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Machine Learning Engineer - Fraud Data
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Staff Machine Learning Engineer - Fraud Data
