MACHINE LEARNING ENGINEER
Descripción de la oferta de empleo
This role involves collaborating closely with the team to analyze documents, extract insights, and automate processes within the supply chain industry.
Key Responsibilities Develop and implement machine learning solutions for extracting structured data from unstructured documents, such as invoices, purchase orders, and shipping manifests.
Create and fine-tune machine learning models tailored to specific supply chain challenges, such as demand forecasting, inventory optimization, or route planning.
Build robust data pipelines to preprocess and clean datasets, ensuring high-quality inputs for machine learning models.
Maintain comprehensive documentation for models and workflows, and share best practices with the team to foster collaboration and innovation.
Qualifications Proficiency in Python and libraries like TensorFlow, or PyTorch.
Experience with data processing frameworks (e.
., Pandas, Spark).
Strong understanding of algorithms, statistics, and optimization.
Experience working with document formats such as PDF, XML, XLSX, and others.
Familiarity with cloud services (AWS, GCP, Azure) for ML deployment.
Bachelor’s or higher in Computer Science, Data Science, or related fields.
Experience working with ERPs such as SAP, Power BI and others is desired.
Experience in the supply chain industry is preferred.
Able to travel to the office in California every other month.
Work Conditions Remote or Hybrid (office space available).
Required to be able to travel to California (main office) every other month.
The candidates need to have a VISA.
Necessary equipment will be provided.
WHAT WE OFFER Competitive salary Major Medical Health Insurance.
15 PTO days since day 1.
Opportunity for advancement & growth in a rapidly expanding team.
Mentorship, learning & education programs Monthly employee events Extended paternal leave Nivel de educación deseada.
Superior - titulado Nivel de experiencia deseada.
Nivel Medio Habilidades.
Python Pandas Pytorch AWS SAP *
Detalles de la oferta
- Confidencial
- 02/01/2025
- 02/04/2025
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