Machine Learning Engineer designing and building machine learning solutions for fintech startup Plaid. Empowering financial freedom through advanced modeling techniques and collaboration.
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.
Requirements
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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