Articul8

Machine Learning Engineer - Data Pipeline

Articul8
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5 months ago
Dublin, CA, USAMid Level / Senior
H1B sponsor

Responsibilities

  • Design and develop data processing pipelines, including data extraction and filtering.
  • Implement machine learning models to enhance data quality and diversity.
  • Lead engineering projects in data acquisition, including web crawling and ingestion.
  • Collaborate with research and technology teams to ensure smooth data flow.
  • Develop and deploy scalable distributed systems for handling large data volumes.
  • Architect algorithms for data indexing and search capabilities.
  • Build and maintain backend services for data storage and synchronization.

Requirements

  • BS/MS/PhD in Computer Science or a related field.
  • Proficiency in at least one deep learning framework, such as PyTorch.
  • Experience in machine learning projects in text or vision.
  • Strong expertise in large stateful distributed systems and data processing.
  • Proficiency in building large-scale data processing pipelines and familiar with distributed workloads.
  • Proficiency in Python and ability to write clean, maintainable code.
  • Excellent problem-solving skills and attention to detail.

Benefits

  • Opportunities for continuous learning and professional development.
  • A diverse and inclusive work environment that encourages creativity.
  • Mentorship and knowledge exchange within the team.

Tech Stack

Apache HadoopDockerKubernetesPythonPyTorchSelenium

Categories

Data Engineering
Articul8

About Articul8

51-200 employees

Articul8 builds an enterprise generative AI platform for regulated industries—finance, aerospace, energy, semiconductor, and supply chain—to turn proprietary data and domain expertise into decisioning and automation. The privately held company, founded in 2024 and headquartered in Dublin, California, sells software and services for deploying domain-specific models with auditability and security. Reported customers include Intel and Franklin Templeton, and it is used by Fortune 500 enterprises.

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