Chief AI/ML R&D Architect

Xplor Technologies; Myrtle Point (OR); Remote; USD 275,000 - 290,000; Full time

Job summary

Xplor Technologies is seeking a senior Head of AI/ML R&D to lead evaluation science, develop predictive models, and guide enterprise ML strategies. The role blends hands-on model work with building scalable, auditable AI systems across multiple business units.

The candidate will own evaluation across agents, design experiments, and drive cost-efficient, trustworthy AI with production-grade monitoring and governance. Remote-friendly, high-impact leadership role.

Qualifications

• 12+ years in data science or ML, with 4+ years leading teams.
• Shipped ML/agentic systems to production recently.
• Strong experimental design and causal inference skills.
• Experience in SaaS or marketplace data at scale.
• Ability to explain model trade-offs to executives.

Responsibilities

• Define enterprise evaluation methodology for agents.
• Own quality signals in telemetry contract: task success, groundedness, hallucination, escalation rates.
• Re-run evals on agent upgrades and catch regressions before customers see them.
• Build churn/retention, payment-recovery, demand models; choose right tool per task.
• Ship production models along the golden path with monitoring for drift.
• Reduce cost per task via distillation, caching, smaller models and prompt optimization.
• Prototype AI-native techniques and publish reference implementations.
• Lead benchmarks for Data-as-a-Service and entity-resolution modeling.
• Raise ML fluency across R&D via training and office hours.
• Review eval designs for BU needs; write production code and eval harnesses.

Skills

Data science leadership

Machine learning

Production ML

Python

SQL

Experimental design

A/B testing

Agentic ML

SaaS analytics

Executive communication

Tools

Snowflake

Feature stores

Datadog

OpenTelemetry

Job description

Xplor Technologies is seeking a senior Head of AI/ML R&D to lead evaluation science, develop predictive models, and guide enterprise ML strategies. The role blends hands-on model work with building scalable, auditable AI systems across multiple business units.

The candidate will own evaluation across agents, design experiments, and drive cost-efficient, trustworthy AI with production-grade monitoring and governance. Remote-friendly, high-impact leadership role.