Top AI & Machine Learning Jobs

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.

Lead Ericsson’s enterprise AI strategy and portfolio across HR, Finance, Sourcing, Customer Support, Marketing, Product Development, Network, and Cloud. Translate business challenges into AI roadmaps, solution architectures, investment cases, and measurable outcomes. Oversee initiatives from opportunity identification through delivery, adoption, and value realization. Prioritize data and AI investments, model ROI and TCO, evaluate vendors and platforms, and advise senior stakeholders on scalable, secure, governed, and commercially viable solutions.

Develop and own scalable AI-enabled software and data engineering solutions for RAN reliability and customer deployments. Build ingestion and processing pipelines, AI-ready datasets, and secure integrations into Git, Gerrit, CI/CD, testing, and development workflows. Transform prototypes into maintainable products while ensuring data quality, traceability, access control, monitoring, and vulnerability management. Collaborate with engineers, data scientists, architects, and product stakeholders, provide mentorship, and promote responsible AI-assisted development.

Develops AI-powered solutions for system verification, testing, and engineering workflows. Responsibilities include building Generative AI, LLM, RAG, and agentic AI applications; integrating AI tools with engineering systems; analyzing quality and testing data; supporting proof-of-concepts; and creating dashboards and visualizations. The role collaborates with verification engineers, test managers, and software developers to improve automation, productivity, and product quality.

Build and prototype AI-powered solutions, intelligent agents, automated workflows, data models, and Power BI dashboards for People Analytics. Extract and transform HR data using tools such as Power Query, Dataflows, Snowflake, and SQL. Apply Python, prompt engineering, and generative AI tools to improve HR insights, data access, decision-making, and employee experience while collaborating across HR and analytics teams.

Build production-grade platforms and governance tooling for AI-assisted software development. Responsibilities include developing reusable standards, registries, APIs, developer tools, AI marketplaces, security and intellectual-property integrations, and CI/CD governance. The role partners across engineering and security teams, takes ambiguous problems from concept through production adoption, and measures platform impact, reliability, and developer experience.

Develop and maintain computer vision and optical inspection systems for automated industrial production. Responsibilities include image processing, machine learning, camera calibration, coordinate transformations, vision hardware selection, Linux and Docker deployment, troubleshooting, dataset management, and production support. The role collaborates with automation, manufacturing, robotics, and software teams while maintaining documentation, version control, experiment reproducibility, and technical standards.

Develop AI-assisted software development and testing automation, operational AI agents, RAG workflows, evaluation systems, monitoring tools, and guardrails. Support observability, incident analysis, system integration, testing, documentation, and process improvement. The role requires Python, SQL, machine learning, MLOps, LLMOps, AgentOps, fine-tuning, and AI agent framework knowledge.

Supports development and validation of cloud-native telecommunications software and AI solutions for software engineering, knowledge management, automation, and developer productivity. Responsibilities include building scripts, tools, dashboards, prototypes, and proof-of-concept implementations; analyzing engineering data; supporting documentation and knowledge repositories; and participating in AI pilots, workshops, hackathons, and stakeholder collaboration.

Develop AI agents, multi-agent workflows, automation tools, dashboards, APIs, and intelligent workflows for quality engineering and software delivery. Integrate AI models, knowledge bases, and automation platforms while prototyping LLM, RAG, knowledge graph, and agentic workflow applications. The intern will contribute to AI transformation initiatives and collaborate with experienced engineers.