R&D Engineer - AI Studio
Canada
Nokia
As a technology leader across mobile, fixed and cloud networks, our solutions enable a more productive, sustainable and inclusive world.You will support the design, implementation, and maintenance of cutting-edge data and AI infrastructure, enabling seamless data processing, governance, and integration for Nokia’s next generation products. This is an opportunity to gain hands-on experience with modern data engineering principles while working in a collaborative and innovative environment.
Responsibilities
Platform Development Support:
- Assist in implementing dynamic data onboarding processes and maintaining the semantic layer exposed to the data catalog.
- Contribute to the integration of data governance policies to ensure compliance with regulatory and business requirements.
Data Infrastructure & Compute Pipelines:
- Help design and maintain pipelines for real-time and batch data processing, supporting MLOps and LLM workflow.
- Collaborate with senior team members to optimize compute environments for hybrid deployments (on-premise and cloud).
Data Lakehouse & Mesh Implementation:
- Work on integrating data lakehouse solutions for scalable analytics.
- Learn and contribute to data mesh principles to enable seamless data combinations for various use cases.
Collaboration & Stakeholder Engagement:
- Support senior engineers in collaborating with cross-functional teams, including product management and architecture.
- Participate in customer engagements to understand and solve industry-specific pai points.
Continuous Delivery & Operational Excellence:
- Assist in ensuring continuous delivery (CD) readiness for platform updates and deployments.
- Contribute to modular and flexible solutions by maintaining clear metadata and content separation.
Develop features and perform project tasks in own areas. Responsible for own code quality, review, testing, troubleshooting, debugging activities in own area. Lead development activities of small/medium complexity features. Support peers in completing feature tasks. Feature Owner/Engineer for small/medium complexity features. Participates and contributes to requirements and design review.
Impact
Accountable for quality and accuracy of own output. Responsible for contribution to teamwork. Errors may have impact on function/project/customer. Usually delivers results with a short-term, operational focus and limited impact on others.
Scope & Contribution
Individual Contributor: Participates as individual contributor to team, usually with limited professional expertise. Makes decisions affecting own work within set parameters, elevates others. Reviews priorities with supervisor. High personal or low collegial interaction. Managerial/Supervisory: May act as Team Leader or Project Leader with some indirect supervisory responsibilities in addition to own work assignments.. Makes decisions that affect own work.
Innovation
Semi routine tasks of moderate complexity requiring some discretion and judgment. Carries out tasks/activities according to assignment and set guidelines. Moderate degree of supervision and coaching needed. Demonstrates initiative and adaptability to changing business environments.
Communication
Explains facts, practices, policies, etc. to external and internal parties. Takes actions which respect to the needs and contributions of others and reaches agreement through flexibility and compromise. Manages situations where there is a common desire to reach solution within a team. Sometimes requires ability to influence others outside of own job area on policies, practices and procedures. Builds cross-cultural knowledge and global mindset.
Key Skills and Experience
- Bachelor’s degree in Computer Science, Data Engineering, or related fields (or equivalen work experience).
- 1-3 years of experience in developing enterprise software, data engineering, cloud platforms, or related field
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and hybrid compute architectures.
- Basic understanding of data governance, lineage, and quality management.
- Exposure to MLOps workflows and LLM deployment is a plus
- Hands-on experience with programming languages like Python, Java, or Go.
- Familiarity with data processing frameworks (e.g., Apache Spark, Kafka, Flink) is desirable.
- Excellent communication and collaboration skills with a desire to learn and grow in the telecom AI space.
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Azure Computer Science Data governance Engineering Flink GCP Java Kafka LLMs ML infrastructure MLOps Pipelines Python R R&D Spark Testing
Perks/benefits: Career development Flex hours
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