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AI R&D Engineer Co-op

Nokia • Mobile Networks • Network Equipment • Master's Degree • 17 days ago
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Salary
≈ $147k – $323k per year (Estimated)
Location
In office (Sunnyvale)

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Oct 1, 2026. Nokia scores A on the Alion truth index.

Overview
Company
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Profile match

Nokia

Nokia is a Finnish telecommunications equipment company founded in 1865 as a paper mill, which became the world's largest mobile phone maker in the 1990s before selling that business to Microsoft in 2014. It now supplies network infrastructure to operators and enterprises, covering radio access equipment for mobile networks, optical and IP routing for transport networks, fixed broadband access, and a technologies division that licenses its cellular patent portfolio. Headquartered in Espoo and listed in Helsinki and New York, it runs Nokia Bell Labs as its research arm and has been expanding into data centre networking as operator spending has slowed.
nokia.com • HQ: Espoo, Finland • Optical Communications • Mobile Networks • Network Equipment • 5000+ employees • Est. 1865
Tech stack of Nokia
Backed by Oak Investment Partners, Mercury Fund

Number of Position(s): 1

Duration: 4 Months

Date: January-May 2027,

Location: Onsite in Sunnyvale, CA

Education Recommendations:

Currently a candidate for a Master’s or PhD in Computer Science, Electrical Engineering, or a closely related field with an accredited school in the US.

  • Design, develop, and deploy advanced AI/ML models and algorithms to analyze and interpret complex data.
  • Design and implement machine learning models to improve a wide range of applications, including search, forecasting, text mining, and more.
  • Develop and implement agentic-based systems for a wide range of applications, including anomaly detection, root-cause analysis, and more.
  • Optimize existing machine learning models and pipelines for performance, scalability, and resource efficiency.
  • Machine learning, optimization algorithms, and deep-learning techniques.
  • Machine learning frameworks (e.g., TensorFlow, PyTorch).
  • Search engines and vector databases, along with their underlying algorithms.
  • Big data frameworks and technologies such as Spark, Kafka, and Cassandra.
  • Excellent communication skills and is a team player
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