R&D Engineer - AI Studio

Family Description

Applied R&D (AR) consists of target-oriented research either with the goal of solving a particular problem / answering a specific question or for multi-discipline design, development, and implementation of hardware, software, and systems including maintenance support. Supplies techno-economic consulting to clients. AR work is characterised by its detailed and complex nature in order to systematically combine existing knowledge and practices to further developing and incrementally improving products, operational processes, and customer-specific feature development.

Subfamily Description

Software (SWA) comprises the definition, specification, and allocation of requirements from different sources utilising knowledge of systems engineering processes (specification & architecture). Contains processing of use case and feature requirements into conceptual models, operational scenarios, technical requirements, and functional description. Covers specification, design, implementation, and unit testing of Software (e.g. device drivers, microcode, hardware-related software & firmware) according to the requirements and architecture defined in the systems engineering process. Covers establishment and maintenance of Software Configuration Management (SCM) practices into software development projects, continuously building and integrating infrastructure tools and systems.

Key Skills and Experience

• Bachelor’s degree in Computer Science, Data Engineering, or related fields (or equivalent 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.

Responsibilities

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.

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 pain 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.