Software Engineer (Python / C++) — ML Platform & Production Integration

Productionize ML algorithms: Take validated Python prototypes from MLEs and implement equivalent, performant C++ modules suitable for integration into production printer software.

Integration and release support: Work with print software and embedded teams to integrate new algorithms, resolve build and runtime issues, and support release validation on hardware or representative test environments.

Testing and quality assurance: Design, implement, and execute test plans (unit, integration, and regression) to verify numerical correctness, edge cases, and parity between Python reference implementations and C++ production code.

Build ML infrastructure and tooling: Develop and maintain Python-based utilities and services that support MLE work—e.g., data download and cataloging, batch preprocessing, dataset versioning, pipeline orchestration, and operational scripts.

Improve data management workflows: Help structure how build sensor data is stored, indexed, retrieved (including from archival storage), and made available for training and evaluation.

Reduce engineering toil: Identify repetitive tasks in the ML workflow (data movement, labeling prep, evaluation runs) and automate them with well-documented, reliable tooling.

Partner with MLEs on specifications: Clarify interfaces, performance requirements, and acceptance criteria so prototypes can be handed off cleanly and integrated without ambiguity.