Top AI & Machine Learning Jobs

Design and deliver production-grade GenAI systems and agents for Telecom OSS/BSS: build RAG pipelines, train and optimize LLM/SLM models, deploy scalable Python services/APIs, and integrate cloud-native ML solutions to drive automation, intelligence, and decisioning at scale.

Internship focused on AI-assisted software development, intelligent operations automation, developer productivity, observability, incident analysis, knowledge discovery, and workflow optimization. The role requires Python, SQL, machine learning fundamentals, and Scikit-learn or TensorFlow experience. Preferred skills include RAG, agent frameworks, evaluation tools, vector databases, Docker, CI/CD, cloud, and Kubernetes. Interns document processes, solve ambiguous problems, learn quickly, and communicate clearly.

Lead and deliver enterprise-scale AI/GenAI projects: translate business problems into scalable solutions, manage cross-functional teams, oversee model development/deployment, define MLOps standards, select LLMs and vector DBs, drive estimations and ROI, ensure compliance and responsible AI, and mentor team members while managing risk and agile delivery.

Develop machine learning and AI solutions, including predictive models, recommendation engines, anomaly detection, statistical models, and deep learning systems. Analyze technical requirements, optimize solutions, manage constraints, and deploy models in on-premise and cloud environments. Collaborate with business leaders to define success metrics and deliver applicable ML solutions. Mentor emerging data scientists and promote machine learning practices across Ericsson.

Develop and deploy advanced AI and machine learning solutions for autonomous 5G telecom networks. Build transformer and LLM applications, agentic workflows, RAG systems, knowledge graphs, and time-series models for network optimization, forecasting, and anomaly detection. Collaborate with telecom, software, data engineering, and product teams to move prototypes into production. Evaluate model performance, improve reliability and scalability, explore emerging AI technologies, and mentor junior data scientists.

Co-op role to design, build and deploy agentic AI systems for telecom: develop AI agents, backend APIs and web frontends, prototype Copilot Studio solutions, analyze network data, containerize and deploy on cloud (Docker/Kubernetes), support CI/CD and collaborate in an Agile team.

Lead design and delivery of enterprise-scale Generative AI systems: define reference architectures, select LLMs and vector databases, build RAG and agentic workflows, embed governance and MLOps, and drive cloud-native scalable deployments while aligning stakeholders and ensuring responsible AI.

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.