Head of AI and ML

Location: Remote, United States. Candidates must be legally authorized to work in the country where the role is advertised.

Salary: USD 275,000–290,000 yearly.

Company

hirify.global provides cloud-based software and secure payment technology for small and medium-sized businesses.

What you will do

• Set the enterprise evaluation methodology for AI agents, including golden sets, sampling, labeling, agreement analysis, LLM-as-judge validation, slice analysis, and statistical thresholds.
• Build and maintain predictive and decision models for churn, retention, payment recovery, demand and capacity forecasting, fraud, and onboarding risk.
• Deploy models through the production golden path with drift monitoring, feedback loops, and quality telemetry.
• Measure model accuracy, cost, and latency; reduce cost per successful task through routing, distillation, caching, smaller models, and prompt/context optimization.
• Prototype agent memory, planning, multi-agent patterns, and synthetic data, turning effective approaches into reference implementations.
• Lead benchmark and index design, entity-resolution modeling, ML reviews, and AI/ML education across the R&D organization.

Requirements

• 12+ years in data science, machine learning, or applied research, including 4+ years leading teams of scientists or ML engineers.
• Production experience training, evaluating, deploying, and maintaining ML models; experience shipping LLM or agentic systems and the evaluation suites that gated them within the last two years.
• Deep experimental design and causal inference experience, including A/B tests, holdouts, uplift modeling, and matched cohorts.
• Strong statistics covering sampling, confidence intervals, calibration, and multiple-comparison risks.
• Current hands-on experience with AI-native tools, agentic coding assistants, MCP, and agent frameworks.
• Production-quality Python and SQL skills, with the ability to credibly review others’ code.
• Experience with SaaS or marketplace data at scale, including multi-tenant, multi-product, and messy data.
• Ability to explain model trade-offs and uncertainty to executives using revenue, margin, and risk outcomes.
• Hands-on production coding, notebooks, evaluation harnesses, model building, and pull-request review are expected; at least 50% of time is hands-on.

Nice to have

• Churn, retention, propensity, or pricing models for subscription or SMB software.
• Payments ML experience in recovery, dunning optimization, fraud, or risk scoring.
• Fine-tuning, distillation, or small-model work focused on reducing inference cost.
• LLM-as-judge design and validation, red-teaming, Snowflake or similar platforms, feature stores, Datadog, or OpenTelemetry.
• Familiarity with NIST AI RMF, ISO/IEC 42001, the EU AI Act, and analytics privacy rules across AU, NZ, US, UK, and EU.
• Published research or open-source work.

Culture & Benefits

• Remote, full-time employment with a hands-on builder and evidence-first working style.
• Responsible for raising ML fluency through training, office hours, and collaboration with business-unit engineers.
• Security- and privacy-minded handling of training data, prompts, tool output, credentials, and customer data.
• Visa sponsorship is not available at hire or later, and contractor or Employer of Record arrangements are not offered.

Hiring process

• Apply through the careers portal or external job boards and answer screening questions directly; emailed applications cannot be uploaded.
• Successful candidates complete background and identity verification checks; video interviews may be recorded during the active hiring process.