ML models Jobs

Financial Connections is Stripe's open banking platform, enabling businesses to securely access consumer-permissioned financial data. Our platform connects to thousands of financial institutions, powering use cases from account verification to risk assessment to personal financial management. Across the Financial Connections Engineering org, we focus on delivering high-quality, enriched bank data at scale — building the ML systems that transform raw financial data into actionable signals for both internal Stripe teams and external merchants. Our ML work spans transaction categorization, risk scoring, data enrichment, and the development of intelligent systems that improve data quality across our network. We operate at the intersection of fintech infrastructure and applied machine learning, solving problems that directly impact Stripe's ability to serve millions of businesses and consumers.

Deepgram is seeking an Applied ML Engineer to focus on deploying their advanced speech models to a variety of edge devices and non-NVIDIA accelerators. This role involves adapting existing models to run efficiently within diverse hardware constraints, including different inference runtimes and operator sets. You will be responsible for optimizing models through techniques like quantization and precision adjustments, validating performance on real hardware, and building robust deployment pipelines for edge targets. This is a hands-on engineering position, distinct from research or cloud-focused roles, aimed at ensuring Deepgram's cutting-edge voice AI can be deployed effectively across a wide range of customer hardware.

$155k - $245k