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Number of Position(s): 1
Duration: 4 Months
Date: May 11 - August 21, 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.
- Experience with: Machine learning, optimization algorithms, and deep-learning techniques.
- Machine learning frameworks (e.g., Tensor Flow, Py Torch).
- 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.
As part of our team, you will:
- 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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About Nokia

Nokia
PublicNokia Corporation is a Finnish multinational telecommunications, information technology, and consumer electronics corporation, originally established as a pulp mill in 1865.
10,001+
Employees
Espoo
Headquarters
Reviews
3.6
25 reviews
Work Life Balance
3.8
Compensation
2.7
Culture
3.9
Career
2.9
Management
2.8
65%
Recommend to a Friend
Pros
Good work-life balance and flexible schedules
Strong company culture and nice people
Excellent benefits and learning opportunities
Cons
Low salary and compensation issues
Limited growth and career opportunities
Frequent leadership changes and lack of direction
Salary Ranges
22 data points
Junior/L3
Mid/L4
Junior/L3 · Global 1830 TAC Engineer
1 reports
$141,314
total / year
Base
$108,703
Stock
-
Bonus
-
$141,314
$141,314
Interview Experience
7 interviews
Difficulty
2.7
/ 5
Duration
14-28 weeks
Offer Rate
57%
Experience
Positive 14%
Neutral 72%
Negative 14%
Interview Process
1
Application Review
2
Technical Phone Screen
3
Technical Interview
4
HR Interview
5
Team Matching
6
Offer
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
Past Experience
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