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 Science, or a related field (or equivalen experience). 5-8+ years of experience in developing enterprise software, data platforms, or AI/ML  solutions. Strong proficiency in programming languages such as Python, Java, or G Experience with cloud platforms (e.g., AWS, Azure, GCP) and hybrid cloud architectures. Familiarity with MLOps frameworks and deploying AI/ML models in production. Hands-on experience with data governance, lineage, and quality management practices. Working knowledge of data lakehouse technologies (e.g., Delta Lake, Apache Iceberg)  and data mesh principles.
 

You will play a key role in the development and enhancement of Nokia's AI Studio platform under the guidance of the Lead Architect. You will collaborate with cross-functional teams to design, build, and deploy cutting-edge features for Nokia’s AI-centric and SaaS product offerings. This role offers the opportunity to work with the latest technologies in AI, MLOps, and cloud computing, contributing directly to transforming the telecom industry.

 Responsibilities:

Platform Development: Implement scalable and efficient components of the AI Studio platform, focusin on data onboarding, processing, and governance. Develop features to support dynamic data onboarding and ensure alignment with the semantic layer architecture. Contribute to the implementation of data governance, ensuring compliance with regulatory and organizational standards. Data Infrastructure & Management: Build and maintain compute pipelines for real-time and batch processing, supporting MLOps and large-scale AI workflow Work on hybrid platform environments, integrating on-premise and cloud-based systems. Contribute to the implementation of data lakehouse solutions for large-scale analytics. Data Store & Mesh Capabilities: Assist in creating data mesh capabilities to enable flexible and effici combination of datasets. Contribute to abstracting data store implementations, supporting seamless integration and flexibilit Collaboration & Stakeholder Engagement: Collaborate closely with product managers and the Lead Architect to ensure the platform meets customer and market requirements. Engage with internal and external stakeholders to gather feedback and refin platform features. Collaborate with internal product teams to identify, onboard, and integrate data sources into the AI Studio platform, ensuring seamless interoperability and alignment with the platform’s architecture. Continuous Delivery & Operations: Write modular, maintainable code supporting continuous delivery and seamless  updates. Ensure adherence to best practices for metadata management and content  modularity. Telecom Industry Focus & Innovation: Apply telecom domain knowledge to develop solutions addressing industry[1]specific need Stay updated with the latest advancements in AI, MLOps, and SaaS to incorporate innovative technologies into the platform.