Join our Team

About the Chance:

Ericsson Enterprise Wireless Solutions (BEWS) is responsible for driving Ericsson's Enterprise Networking and Security business. Our expanding product portfolio covers wide area networks, local area networks, and enterprise security. We are the #1 global market leader in Wireless-WAN enterprise connectivity and are rapidly growing in enterprise Private 5G networks and Secure Access Services Edge (SASE) solutions.

What Will You Do:

Lead the design and implementation of machine learning and statistical models to solve complex business problems across multiple domains.
Architect and build Agentic AI systems - including multi-agent pipelines, autonomous reasoning loops, tool-using agents, and agent orchestration to enable proactive, self-directed network operations.
Design and deploy LLM-powered applications including RAG pipelines, fine-tuned domain models, prompt engineering strategies, structured output generation, and evaluation frameworks (LLM-as-judge, RAGAS, etc.).
Collaborate with cross-functional teams - data engineers, product managers,



and architects - to identify high-impact opportunities for AI-driven solutions and translate them into production-grade systems.
Perform data exploration, feature engineering, and dataset curation to support both classical ML model development and LLM grounding/context pipelines.
Evaluate model performance using rigorous metrics, and ensure interpretability, fairness, and robustness across model types - from tree-based models to transformer architectures.
Contribute to reusable AI frameworks, internal tooling, and shared libraries to raise engineering velocity across the team.
Stay at the forefront of AI/ML research - actively tracking arXiv, open-source releases, and industry developments

What You Will Bring:

8–14 years of applied Data Science and Machine Learning experience, with demonstrated progression in scope and complexity of owned systems.
Deep expertise in classical ML - regre

📌 Senior Data Scientist II (India)
🏢 Ericsson
📍 India