Senior ML Engineer - Embedded Insights (0-to-1 Product)

Plaid; San Francisco (CA); Presencial; USD 229 000 - 315 000; Tempo integral

Resumo da oferta

Plaid seeks a Senior Machine Learning Engineer to shape our Embedded Insights products. You will build ML-powered features for a consumer-facing Plaid App and help establish product-market fit for a new business line.

You will collaborate with product, data science, and engineering to translate opportunities into robust ML systems delivering measurable customer value. You will work with data scientists to define success metrics, establish guardrails, and partner with ML engineers to

Qualificações

• 6+ years of ML experience in production systems.
• Experience deploying models to customer-facing products.
• Strong SQL and Python skills.

Responsabilidades

• Build ML-based features for a 0-to-1 consumer-facing product.
• Partner with product managers to translate requirements into ML problems.
• Iterate and experiment to drive product-market fit for a new business line.
• Define success metrics and guardrails with Data Scientists for ML features.
• Collaborate with ML engineers to build data feedback loops.
• Analyze Plaid’s datasets to identify high-impact ML opportunities.
• Productionize models with product teams and deploy to customers.
• Maintain model health with retraining cadences, metrics, alerts, dashboards.
• Communicate technical decisions clearly to cross-functional partners.

Conhecimentos

ML experience

Analytical thinking

Cross-functional collaboration

Communication

Formação académica

Advanced degree in a relevant field

Ferramentas

Python

SQL

Data visualization tools

Descrição da oferta de emprego

Plaid seeks a Senior Machine Learning Engineer to shape our Embedded Insights products. You will build ML-powered features for a consumer-facing Plaid App and help establish product-market fit for a new business line.

You will collaborate with product, data science, and engineering to translate opportunities into robust ML systems delivering measurable customer value. You will work with data scientists to define success metrics, establish guardrails, and partner with ML engineers to