Data & AI Engineer - Intelligent Systems & ML Platforms

Cisco

Hillsboro (OR)

On-site

USD 110,000 - 160,000

Full time

14 days+

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Benefits offered by this job

Health Insurance
Dental Insurance
Vision Insurance
401k
Paid Parental Leave
Short and Long-term Disability/Coverag
Life Insurance
Paid Time Off
Stock Options

Job summary

Cisco is seeking a data engineer to build scalable data pipelines and analytics platforms that power machine learning initiatives in Hillsboro, Oregon. You will contribute to AI-enabled insights that drive operational excellence across Cisco’s business groups.

The role requires strong Python programming, experience with ML frameworks, and familiarity with distributed data processing technologies. Collaborative, cross-functional work with data engineering and analytics teams is essential.

Qualifications

  • Candidates should have a relevant degree or certification along with experience in programming and data systems. Proficiency in Python and familiarity with machine learning frameworks and distributed data processing technologies are essential.

Responsibilities

  • Develop scalable data pipelines and analytics platforms to support machine learning initiatives.
  • Enable Cisco's business groups to leverage AI and data-driven insights for operational excellence.

Skills

Python
Machine Learning
TensorFlow
PyTorch
Scikit-learn
Apache Spark
Hadoop
Apache Flink
Docker
Kubernetes
Data Structures
Distributed Systems
Cloud Platforms
AI
Data Engineering
Analytics

Education

Bachelor's degree in Computer Science or related field

Tools

Docker
Kubernetes
Apache Spark
Hadoop
Apache Flink

Job description

Cisco is seeking a data engineer to build scalable data pipelines and analytics platforms that power machine learning initiatives in Hillsboro, Oregon. You will contribute to AI-enabled insights that drive operational excellence across Cisco’s business groups.

The role requires strong Python programming, experience with ML frameworks, and familiarity with distributed data processing technologies. Collaborative, cross-functional work with data engineering and analytics teams is essential.

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