Entry Level: Data Scientist

About this job

Join our Team About this opportunity: Are you a recent graduate passionate about AI and the new technologies in this area? Join our Ericsson Radio Software AI Team planning, introducing and promoting today’s and future AI technologies. To achieve our goals, we collaborate closely with internal and external partners, to introduce the state of the art AI technology and enhance the Radio Product Development beyond current capabilities. You’ll be part of a team of about 5 colleagues with a mix of junior and senior experience and diverse backgrounds. We are also working together with teams from Vietnam and Türkiye, to operate our AI Infrastructure and Data platform. As a new graduate, you’ll be encouraged to explore these areas, and we’ll align your responsibilities with your interests and development goals. What you will do: Operate the RUSW AWS account and support AI workloads across cloud and on-premises environments. Collaborate with the Data Platform team to enable AI access to semantic layers, knowledge graphs, metadata, and enterprise data products. Establish AI evaluation capabilities, including benchmarks, test datasets, quality metrics, and regression testing. Manage the lifecycle of AI agents and models, including versioning, rollout, rollback, experimentation, and retirement. Help transform existing workflows into AI-native processes. Design context-engineering and knowledge-management practices that enable agents to use reliable, up-to-date information. The skills you bring: A degree in Computer Science, Software Engineering, AI, or a related field, with a strong interest in generative AI and agentic systems. Knowledge of cloud and platform engineering, preferably AWS, Kubernetes, Docker, CI/CD, and Infrastructure as Code. Understanding of distributed systems, APIs, microservices, event-driven architectures, or workflow orchestration. Interest in knowledge graphs, ontologies, vector databases, semantic APIs, and retrieval-augmented generation. Familiarity with agent engineering concepts such as multi-agent systems, tool calling, MCP, LangGraph, or human-in-the-loop workflows is an advantage. Experience or interest in LLMs, prompt engineering, structured outputs, evaluation, guardrails, and responsible AI. Strong analytical, collaborative, and problem-solving skills, with the ability to work independently and learn quickly.

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