Top AI & Machine Learning Jobs

Support AI proofs of concept, prototypes, and digital transformation projects. Participate in requirements and design discussions, preprocess data, engineer features, contribute to model architecture decisions, implement and evaluate AI models, and integrate software components into complete solutions. The role requires software development, data analysis, version control, autonomous problem-solving, and bilingual French-English communication.

Design, architect, develop and operate end-to-end AI/ML solutions and scalable data pipelines. Lead solution roadmaps, deploy ML/DL models to cloud/edge, manage MLOps, support and maintain solutions, and perform operational tasks like data loading, batch scheduling, monitoring, and incident analysis.

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

Develop and test AI Agent tools for board-level power supply design, including topology selection, component recommendations, and design-rule checks. Analyze requirements, engineer prompts, verify functionality, evaluate power solutions, test components, maintain a power-design knowledge base, and prepare documentation and reports.

Design and deliver production-grade generative AI applications, AI agents, enterprise copilots, and intelligent automation for telecom OSS/BSS. Build Python-based AI services using LLMs, RAG, Graph RAG, knowledge graphs, vector databases, and cloud AI platforms. Train, fine-tune, optimize, and evaluate language models while developing scalable, cloud-native deployments with APIs, containers, Kubernetes, and MLOps. Collaborate with technical and business stakeholders to deliver enterprise AI solutions.

Support the Beijing Radio R&D team in designing, developing, and implementing AI models and algorithms for telecommunications applications. The intern will gain hands-on experience with advanced AI technologies while contributing to real-world connectivity projects. Responsibilities include applying machine learning concepts, programming in Python or other mainstream languages, collaborating with team members, analyzing problems, and learning quickly in a fast-paced environment.

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

Develop and maintain AI agents and generative AI solutions to support engineering and verification tasks. Integrate AI with tools, databases, and APIs, automate workflows, analyze user requirements, evaluate new AI technologies, and produce documentation and demos.

Work on designing, building, and evaluating AI agents using LLMs, RAG, and agent frameworks. Integrate models, create tool-calling workflows, implement backend services and APIs, build tests/benchmarks, analyze failures, and prototype enterprise AI solutions while collaborating with engineers and stakeholders.

Design, develop and systemize AI/ML-enabled RAN functions for 5G/NR networks. Build and optimize ML models for real-time, resource-constrained telecom platforms, integrate prototypes into production RAN software, design experiments and validation strategies, and improve network performance through data-driven solutions and lifecycle best practices.