Junior Applied AI/ML Engineer

Network Infrastructure Optical Service Practice, part of the Network infrastructure – Global Customer Engineering organization, provides expert customer support for optical networks, covering design, integration, transformation, and migration. The team drives digital transformation through solutions like Digital Twin, process automation, and advanced reporting while AI/Machine Learning for Optical Automation team provides data science components for all solutions. 

The role focuses on defining and implementing AI / Machine Learning bases automation solutions in different stages of our services lifecycle including planning designing, deploying, and optimizing optical networks. Ideally, the role bridges deep mathematical modeling and real-world AI implementation.

You’ll cover a critical role within Network Infrastructure Optical services, aimed at defining, developing and expanding usage of automation within optical professional services engineering community through extensive application of AI and ML to automation processes. The role will be responsible for defining and developing AI and ML solutions for automation that align with our strategic objectives, enhancing our offerings and market creation in the automation space.

You will:

• Contribute to analyzing automation processes for understanding Artificial Intellgence/Machine Learning introduction opportunities and related benefits
• Contribute to developing Artificial Intelligence/Machine Learning prototypes and productized solutions as part of more general automation solutions
• Contribute to integration of developed artifacts into automation solutions
• Contribute to solution validation strategy and test list
• Execute internal system integration tests
• Develop domain knowledge in Optical Transport Networks 
• Develop domain knowledge in procedures for network transformation
• You will develop solid professional expertise in creating AI/ML solutions for domain problems, from concept to functional, performance and orchestrated containerized implementation using cloud native technologies
• You will engage with applied research topics and contribute to innovative approaches in solving domain-specific problems using AI/ML
• You will develop a strong professional foundation in optical transport technologies

General

• Master's degree in Computer Science with solid background in Data Science and Machine Learning Engineering 
• English written and spoken is a MUST
• The ability and willingness to travel as per project requirements.

Key skills – Foundational Artificial Intelligence/Machine Learning Engineering

• Statistical Machine Learning (supervised, unsupervised, Reinforcement Learning, Natural Language Processing, time series forecasting)
• DNN and frameworks (TensorFlow, PyTorch, Keras)
• Background in Statistics and Optimization
• Data Wrangling, Feature Engineering, Model Validation and Tuning
• Containerization and Orchestration (Docker, Docker networks)
• CI/CD Tools (GitLab, Artifactory, Jira, Confluence)
• Fluent in Python, Knowledge of C++, SQL
• Linux and shell scripting knowledge
• Knowledge (academic and possibly hands on) required.

Key skills – Generative AI & Agentic Systems

• Generative Artificial Intelligence (Large Language Models, RAG, transformer architectures)
• Agentic Systems Frameworks (e.g., CrewAI, LangGraph, etc.)
• Design and Tuning of Scalable Data Pipeline
• Familiarity with APIs (REST - Representational State Transfer, gRPC - google Remote Procedure Call) and microservices
• Knowledge (academic and possibly hands on) is a strong plus.

Soft Skills

• Team player / innovative / problem solver / self-motivated / target oriented
  In particular
  • Curious and self-motivated, comfortable bridging theory and implementation
  • Capable of moving from abstract problem framing to concrete, testable solutions
  • Comfortable with mathematical modeling and problem solving, but also confident in writing robust, production-grade code

Nice to have:

• Orchestration with K8s
• Distributed data wrangling on Big Data (e.g., Spark) 
• Data Pipelines tooling (Airflow, Kafka)
• Front-End Technologies for UI development (CSS - Cascading Style Sheets, html, JavaScript, php)
• MLOPS tooling - Machine Learning Operations
• Network security know-how (e.g. vulnerability scanning tools, cybersecurity concepts…)
• Telecommunications knowledge

Come create the technology that helps the world act together

Nokia is committed to innovation and technology leadership across mobile, fixed and cloud networks. Your career here will have a positive impact on people’s lives and will help us build the capabilities needed for a more productive, sustainable, and inclusive world.
We challenge ourselves to create an inclusive way of working where we are open to new ideas, empowered to take risks and fearless to bring our authentic selves to work

What we offer
 
Nokia offers continuous learning opportunities, well-being programs to support you mentally and physically, opportunities to join and get supported by employee resource groups, mentoring programs and highly diverse teams with an inclusive culture where people thrive and are empowered.

Nokia is committed to inclusion and is an equal opportunity employer

Nokia has received the following recognitions for its commitment to inclusion & equality:

• One of the World’s Most Ethical Companies by Ethisphere
• Gender-Equality Index by Bloomberg
• Workplace Pride Global Benchmark

At Nokia, we act inclusively and respect the uniqueness of people. Nokia’s 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.

Join us and be part of a company where you will feel included and empowered to succeed.