Staff Applied Machine Learning Engineer (Fintech)

TL;DR

Staff Applied Machine Learning Engineer (Fintech): Building and operating production ML systems that transform customer behavior and product context into trusted signals with an accent on ranking, retrieval, and recommendation systems. Focus on designing composable signal interfaces, ensuring system reliability, and evaluating long-term business impact across diverse financial products.

Location: Must be based in the United States

Salary: $276,800–$415,200 USD

Company

hirify.global builds simple, powerful tools that make progress towards an economy that is truly open to all, including brands like Square, Cash App, Afterpay, and TIDAL.

What you will do

• Build and operate production ML systems that turn customer and product context into trusted signals, rankings, and recommendations.
• Design production data and signal contracts that define freshness, provenance, confidence, and calibration for downstream consumers.
• Own ranking, retrieval, and decision systems end-to-end, from feature generation through serving, experimentation, and feedback loops.
• Evaluate customer and business impact, including trust, fairness, risk, compliance, and long-term engagement.
• Partner across product, growth, data, and risk teams to translate ambiguous goals into measurable ML system designs.
• Use AI and agents to accelerate development, testing, and operations while exposing reusable capabilities to internal tools.

Requirements

• 12+ years of experience building and operating production software and ML systems for business-critical products.
• Deep expertise in intelligent systems such as ranking/retrieval, recommendations, search, personalization, or customer intelligence.
• Strong production ML judgment across feature pipelines, model serving, experimentation, and monitoring.
• Ability to evaluate impact beyond short-term conversion, including trust, fairness, and risk.
• Experience using AI-assisted engineering tools with appropriate verification and testing.
• Must be authorized to work in the United States.

Nice to have

• Experience with semantic retrieval, embeddings, two-tower models, or LLM-powered decision systems.
• Experience with multi-objective optimization, counterfactual evaluation, or long-term holdouts.
• Experience building reusable feature/signal platforms or agent-assisted operations.

Culture & Benefits

• Remote work flexibility.
• Comprehensive medical insurance and modern family planning.
• Retirement savings plans.
• Flexible time off.
• Commitment to an inclusive and fair workplace.