Top AI & Machine Learning Jobs

Six-month AI/ML internship to research and implement MARL communication architectures and semantic communication protocols for Physical AI. Design experiments, develop world-model-based representations, evaluate under realistic wireless constraints using MARL benchmarks and Mobile-Env, and contribute to research publications.

The role involves designing and developing AI solutions, optimizing AI models, analyzing data for insights, and collaborating with teams to integrate AI into products.

Participate in deployment, configuration, testing and troubleshooting of RAN nodes. Develop automation scripts, integrate AI/LLM-driven use cases and collaborate on 5G feature testing. Maintain documentation and report results.

Lead AI strategy for the NetCloud platform, owning roadmaps for AIOps, LLM assistants, agentic workflows, MCP/API extensibility, and cross-functional alignment to ship AI-driven features that improve reliability, automate remediation, and deliver measurable customer value.

Lead and execute an AI-driven automation and data strategy for global hyperscaler delivery programs. Define roadmap, prioritize use cases, lead a matrixed global team to build scalable automation tooling, enable AI/ML-driven operations, define data standards and metrics, and partner with engineering and commercial teams to industrialize and measure automation ROI.

Design and architect AI-driven solutions at Ericsson, focusing on Generative AI and Agentic systems, while mentoring teams and collaborating on product integration.

Support development, testing, and integration of AI solutions on Microsoft/Azure AI platforms. Prototype generative and agent-based AI use cases, perform basic data analysis and model evaluation, and help build internal tools or web interfaces while collaborating with cross-functional teams.

Design and evolve platform and data architectures to enable scalable AI/ML deployment (MLOps/LLMOps), data ingestion and streaming, and IDP/Golden Path platform engineering. Lead architectural studies, collaborate cross-functionally, define technology strategy, and run proofs-of-concept while ensuring scalability, security, and operational efficiency.

The Principal AI Compiler Engineer designs hardware for AI, ensuring models translate effectively to silicon and perform optimally in 5G applications.

The Principal AI Model Architect's role includes optimizing model architectures for new hardware, translating AI algorithms into hardware specifications, and projecting performance for silicon design.