Staff AI Engineer
Nokia
Software Engineering, Data Science
United States
Posted on Nov 23, 2025
The Nokia CNS AI R&D (AIRD) team's mission is to invent and deploy the next generation of intelligent, generative AI, and ML technologies that will define the future of Nokia. This team represents a major investment and consolidation of our AI efforts, created to move from siloed features to a unified and powerful product & platform portfolio. We are the future powerhouse for driving the of Nokia's future business growth and building a suit of technologies that is recognized externally as best-in-class.
About Nokia
Join us in creating the technology that helps the world act together.
We are a B2B technology innovation leader, pioneering networks that sense, think and act™, putting the world’s people, machines and devices in sync to create a more sustainable, productive and accessible future.
About the Business Group
In Cloud and Network Services, as Nokia's growth engine, we create value for communication service providers and enterprise customers by leading the transition to cloud-native software and as-a-service delivery models. Our inclusive team of dreamers, doers and disruptors push the limits from impossible to possible.
Our recruitment process
We act inclusively and respect the uniqueness of people. Our employment decisions are made regardless of race, color, national or ethnic origin, religion, gender, sexual orientation, gender identity or expression, age, marital status, disability, protected veteran status or other characteristics protected by law. We are committed to a culture of inclusion built upon our core value of respect.
If you’re interested in this role but don’t meet every listed requirement, we still encourage you to apply. Unique backgrounds, perspectives, and experiences enrich our teams, and you may be just the right candidate for this or another opportunity.
The length of the recruitment process may vary depending on the specific role's requirements. We strive to ensure a smooth and inclusive experience for all candidates. Discover more about the recruitment process at Nokia.
Some of our benefits in US:
- Corporate Retirement Savings Plan
- Health and dental benefits
- Short-term disability, and long-term disability
- Life insurance, and AD&D – Company paid 2x base pay
- Optional or Supplemental life and AD&D insurance (Employee/Spouse/Child)
- Paid time off for holidays and Vacation
- Employee Stock Purchase Plan
- Tuition Assistance Plan
- Adoption assistance
- Employee Assistance Program/Work Life Resource Program
The above benefits exclude students.
Disclaimer for US/Canada
Nokia Maintains broad annual base salary ranges for its roles in order to account for variations in knowledge, skills, experience and market conditions, and with consideration to internal peer equity. Check the salary ranges in the job info section for this role.
All North America job posts will post for a minimum of 7 calendar days and up to 180 days or until candidate/s identified.
As a Staff AI Engineer at Nokia, you will be responsible for the R&D of cutting-edge AI solutions that can effectively leverage Generative AI, Agents, Deep Learning and Machine Learning to power a wide range of products & platforms – from analytics to security to telecom core capabilities. Nokia relies on innovative AI research and applications that you will help us build.
- 3-5 years of relevant machine learning experience
- MS or PhD in Computer Science or Engineering, Mathematics, or a related field.
- Experience with machine learning, optimization algorithms, deep-learning techniques
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch).
- Experience with search engines and vector databases, along with their underlying algorithms.
- Experience with big data frameworks and technologies such as Spark, Kafka, Cassandra.
- 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-case analysis and more.
- Optimize existing machine learning models and pipelines for performance, scalability, and resource efficiency.