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Designs, builds, tests, and maintains scalable production data pipelines and infrastructure. Owns data workflows from ingestion through transformation, storage, and delivery; integrates varied data sources; develops data models and warehouse or lakehouse structures; and ensures data quality through monitoring, validation, and alerting. The role also diagnoses pipeline issues, contributes to architecture, evaluates cloud and data technologies, supports disaster recovery, and develops reliable datasets for data scientists and machine learning systems.

Develop and validate statistical, forecasting, predictive, simulation, optimization, and machine learning models for real-world manufacturing and business problems. Translate business questions into analytical solutions, engineer features, design experiments, evaluate model performance, and collaborate with engineering teams on production deployment. Monitor models, communicate findings to technical and non-technical stakeholders, and provide recommendations that improve operations, increase revenue, or reduce costs.

Design, build, test, deploy, and support reliable production software enabling AI solutions in manufacturing environments. Responsibilities include developing services, APIs, tooling, integrations, and system components; translating requirements into technical solutions; contributing to architecture; improving reliability, performance, observability, and security; participating in code reviews; collaborating with data and business teams; and mentoring less experienced engineers.

Join the EDGE team to develop and manage embedded software solutions for industrial edge devices, ensuring performance, reliability, and security across diverse environments. Responsibilities include architecting systems, developing a data pipeline, and collaborating with OEM partners.