Senior Product Manager

Machinify

About The Position

Machinify is seeking a Product Manager, Product Intelligence, Evals & Telemetry to build and scale the analytical and measurement backbone of our Pay platform. This role owns how we instrument products, evaluate AI-driven capabilities, and transform signals from usage, model performance, and customer operations into insights that accelerate innovation, reduce time-to-value, and maximize customer ROI. You will operate at the intersection of Product, Engineering, Data Engineering, Data Science, and Customer Operations—bringing strong technical depth and product judgment to shape foundational capabilities that power decision-making and continuous improvement across the company.

Requirements

5+ years of Product Management experience building technically complex, data-intensive, or AI-powered products. Exceptional early career professionals welcome
Demonstrated ownership of product analytics, telemetry, experimentation, or evaluation systems.
Strong technical fluency: able to reason about data models, event pipelines, APIs, ML evaluation approaches, and system architecture.
Experience working closely with Data Engineering and Data Science on platform-level capabilities.
Track record of balancing short-term impact with long-term platform investments.
Comfort translating ambiguous problems into clear technical and product requirements.
Strong UX instincts and experience partnering with Design on data-heavy workflows.
High ownership, bias to action, and ability to drive initiatives from concept to measurable impact.
Excellent written and verbal communication and strong stakeholder management skills.

Responsibilities

Own the end-to-end vision and roadmap for product analytics, telemetry, and AI evaluation infrastructure.
Define canonical event schemas, metric definitions, and data contracts for capturing user behavior, workflow performance, model outputs, and business outcomes.
Partner with Data Engineering to design scalable data pipelines, storage, and transformations that ensure high-quality, low-latency, and trustworthy product data.
Partner with Data Science to design offline and online evaluation frameworks for AI/ML features (e.g., golden datasets, automated scoring).
Specify and drive internal tooling (dashboards, exploration tools, alerting, experimentation platforms) that enable fast diagnosis and informed product decisions.
Translate customer and operational pain points into measurable hypotheses, experiments, and product requirements.
Drive continuous improvement loops: instrument → measure → learn → ship → validate.
Influence product strategy through evidence-backed insights and clearly articulated trade-offs.
Lead cross-functional execution, aligning engineering, data, design, and operations around shared outcomes.
Develop deep understanding of Machinify Pay's architecture and data flows to assess feasibility, sequencing, and technical risk.