Machine Learning Engineer
SweedFull Time
Mid-level (3 to 4 years)
The ideal candidate will have experience organizing data and developing machine learning models on geometric data. Experience with machine learning pipelines, particularly on geometric data, and experience working in a production software engineering environment are required. Strong programming skills in Python or C++ are necessary. Experience with powder bed fusion based manufacturing, knowledge of manufacturing data workflows, IoT sensor data, or industrial automation systems are considered a plus.
The machine learning engineer will kick-start efforts to predict the printability of complex part geometry. This includes working with process, preprint, and applications teams to develop ML models using various sensors to predict printability. The role also involves defining and maintaining data collection processes, designing and developing databases for data ingestion, storage, and retrieval, and deploying developed models into production with the preprint team.
Metal additive manufacturing solutions provider
Velo3D specializes in metal additive manufacturing, also known as 3D printing, providing a complete solution for creating complex metal parts that traditional manufacturing cannot achieve. Their offerings include advanced 3D printers, software, and support services tailored for high-tech industries like aerospace and energy, which require precise and specialized components. Velo3D's technology allows clients to innovate more quickly and efficiently by enabling the production of intricate designs. The company differentiates itself from competitors by focusing on high-end printers, particularly the Sapphire series, and by continuously expanding its capabilities through the qualification of new materials, such as copper alloys. Velo3D's goal is to drive growth in the advanced manufacturing sector by offering both product sales and ongoing service contracts, ensuring a steady revenue stream while meeting the increasing demand for customized parts.