Data Scientist

Ericsson is looking for a passionate Data Scientist to build next-generation AI solutions for Telecom OSS/BSS. You will design and deliver production-grade AI Agents, Enterprise Copilots, and intelligent automation using Generative AI, LLMs/SLMs, Knowledge Graphs, and cloud-native AI platforms to solve complex business problems at scale.

Responsibilities

Design and develop production-grade GenAI applications and AI Agents.; Build Enterprise Copilots using LLMs/SLMs, MCP, RAG, and Graph RAG.; Develop Knowledge Management solutions leveraging Knowledge Graphs, vector databases, and enterprise data.; Train, fine-tune, optimize, and evaluate LLMs/SLMs for domain-specific use cases.; Build scalable Python-based AI services and APIs.; Deliver enterprise AI solutions using AWS Bedrock and/or Google Vertex AI.; Collaborate with architects, data engineers, and business stakeholders to deliver AI-driven business outcomes.

Requirements

Strong foundation in Statistics, Machine Learning, Deep Learning, NLP, and Generative AI.; Expert Python programming with experience building production-grade AI/GenAI applications.; Hands-on experience with AI Agents, Multi-Agent Systems, Enterprise Copilots, RAG, Graph RAG, embeddings, vector databases, and agent orchestration frameworks.; Strong understanding of Knowledge Management, Knowledge Graphs, Semantic Search, and enterprise retrieval architectures.; Experience developing MCP (Model Context Protocol)-based applications.; Experience training, fine-tuning, and optimizing LLMs/SLMs.; Expertise in AWS Bedrock and/or Google Vertex AI, including AgentCore/Agents, Knowledge Bases, Guardrails, Prompt Management, Model Customization, Vertex AI Agent Builder, and enterprise AI deployment.; Experience with cloud-native development, APIs, containers, Kubernetes, and MLOps.

Nice to have

Telecom OSS/BSS domain knowledge.; Experience with AI Reasoning, Agent Memory, Planning, and Tool Use.; Knowledge of AI Observability, Explainability, Responsible AI, and Governance.; Experience with Databricks, Snowflake, MLflow, or similar AI platforms.; Master's/Ph.D. in Computer Science, AI, Data Science, or a related field is preferred.; Publications, patents, or open-source contributions in AI/ML are an added advantage.