Nokia
Overview
Position:
AI R&D Engineer Co-op Number of Position(s):
1 Duration:
4 Months Date:
January 12–May 22, 2026 Location:
Onsite Education Recommendations: Currently a candidate for a Master’s or PhD degree in Computer Science or Engineering, Mathematics, or a related field with an accredited school in the US. Qualifications
Experience with:
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. Responsibilities
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.
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Position:
AI R&D Engineer Co-op Number of Position(s):
1 Duration:
4 Months Date:
January 12–May 22, 2026 Location:
Onsite Education Recommendations: Currently a candidate for a Master’s or PhD degree in Computer Science or Engineering, Mathematics, or a related field with an accredited school in the US. Qualifications
Experience with:
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. Responsibilities
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.
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