Teams at Apkudo

Leads end-to-end technical solution and implementation projects, including scoping, planning, budgets, deliverables, configuration, data triage, reporting, and signoff. Translates customer workflows into business and technical requirements, partners with Product and Engineering on roadmap decisions, supports sales pursuits and proof-of-concepts, and drives cross-functional collaboration. Ensures solutions align with customer objectives while balancing scalable product capabilities against custom implementations.

Lead development of Device OS platform infrastructure connecting industrial machines and applications to Apkudo. Own integration services, APIs, software and model deployment, staged rollouts, rollback, fleet monitoring, telemetry, diagnostics, and operator-facing control surfaces. Partner with robotics, AI, design, and operations teams to create reliable interfaces and deployment workflows for heterogeneous distributed devices.

Build and maintain computer vision and machine learning pipelines for automated device inspection, grading, and quality assessment. Responsibilities include data preparation, feature engineering, model training and evaluation, production Python development, monitoring, annotation workflows, documentation, code reviews, and collaboration with product and operations teams. The role supports the full ML lifecycle and offers increasing ownership under senior engineering guidance.