Full TimeENNorth America
As a Machine Learning Test Capability Engineer at Nokia, you will join a dynamic team focused on advancing optical communication technologies through intelligent, data-driven test methods. Reporting directly to the Sr. Manager of Test Capability Engineering, you will work alongside a team of test capability engineers embedded across our coherent pluggable product lines. Your role bridges big data infrastructure, machine learning, and manufacturing test — translating the rich datasets generated by our test platforms into predictive models, automated diagnostics, and yield intelligence. The collaborative environment fosters open communication, where your insights and feedback are valued and drive meaningful change. Enjoy competitive compensation, a comprehensive benefits package, and opportunities for professional growth in a state-of-the-art facility.
We are looking for recent or upcoming graduates (MS or PhD) in Data Science, Machine Learning, Electrical Engineering, or Computer Science.
Design and deploy machine learning and big data solutions that integrate directly with Nokia’s manufacturing test platforms for coherent pluggable products.
Partner with test capability engineers to identify opportunities where predictive modeling, anomaly detection, and statistical inference can improve yield, reduce cycle time, and accelerate fault isolation.
Build and maintain scalable data pipelines that aggregate and normalize test data across manufacturing sites and product families.
Develop ML models for test outcome prediction, failure classification, and early warning of process drift or hardware degradation.
Apply unsupervised and supervised learning methods to identify latent patterns in optical transceiver test data.
Collaborate with cross-functional stakeholders — including development, manufacturing, and product engineering — to integrate ML insights into actionable test platform changes.
Establish and maintain best practices for model validation, versioning, and deployment within the test environment.
Communicate findings clearly to technical and non-technical audiences, including engineering leadership.
You have:
MS or PhD in Data Science, Machine Learning, Electrical Engineering, Computer Science, Applied Mathematics, Statistics, or a related quantitative field.
Strong foundation in machine learning methods: supervised/unsupervised learning, regression, classification, clustering, anomaly detection.
Proficiency in Python and data science stack (pandas, scikit-learn, PyTorch or TensorFlow, etc.).
Proficiency in SQL (MySQL or other relational database frameworks) for large-scale data extraction and analysis.
Experience with JMP or similar statistical analysis and visualization platforms.
Demonstrated ability to work with high-volume, real-world datasets in a production or research setting.
Strong data visualization and communication skills.
It would be nice if you also had:
Experience with big data platforms (Spark, Databricks, Azure ML, etc.).
Previous Infinera or Nokia internship experience.
Exposure to Azure DevOps, Bitbucket, or similar source control platforms.
Knowledge of statistical process control (SPC) or manufacturing yield modeling.
Experience deploying ML models in operational or embedded environments.
Familiarity with VB.net or similar programming languages used in test automation.
Nokia is a global leader in connectivity for the AI era. With expertise across fixed, mobile and transport networks, powered by the innovation of Nokia Bell Labs, we’re advancing connectivity to secure a brighter world.
Learn more about life at Nokia.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.
