Top AI & Machine Learning Jobs

Conduct a master’s thesis on improving the energy efficiency of AI-generated software. Design and implement a workflow integrating coding agents with energy analysis and profiling tools, then evaluate it through experiments. Potential outcomes include a methodology for measuring software sustainability, an energy-feedback architecture, optimization techniques, benchmarks, experimental results, and recommendations for energy-aware agentic development.

Master’s thesis focused on building an AI-agent harness for autonomous antenna and hardware design. The work includes defining requirements and metrics, generating parametric geometry, driving electromagnetic simulations through APIs, extracting results, validating designs, maintaining run logs, and optimizing filter-to-antenna interfaces under manufacturability constraints. The thesis compares agent-generated designs with conventional fixed-impedance designs and concludes with a report and presentation to Ericsson hardware teams.

Build a machine-learning framework that ranks verification events by diagnostic relevance in failing ASIC tests. The project uses real Ericsson production regression data to train and evaluate models, compare results with expert assessments, reduce manual triage effort, and develop auditable testbench quality scoring. Work includes data preparation, event correlation, model evaluation, and optional early failure-pattern detection.

Conduct research on fine-tuning time-series foundation models for energy-efficient orchestration of cloud-native 5G networks. The work includes collecting NF telemetry, benchmarking foundation models against classical baselines, evaluating zero-shot and few-shot forecasting, exploring parameter-efficient fine-tuning, analyzing model generalization, and recommending integration into energy-aware orchestration pipelines.

Designs, develops, deploys, and optimizes AI and machine learning solutions for business and technical challenges. Responsibilities include anomaly detection, predictive maintenance, root-cause analysis, chatbot operations, digital-twin development, closed-loop simulations, model evaluation, cloud deployment, and cross-functional integration. The role also researches emerging AI techniques, analyzes data, documents architectures, and troubleshoots conversational agents.

Master’s thesis exploring how AI and Large Language Models can analyze power-saving features in Ericsson 4G and 5G radios. The work includes studying radio behavior, developing AI methods to recognize and reason about multiple energy-performance features, detecting anomalies, and evaluating AI-assisted workflows for earlier issue identification and faster feature development.

Conduct a master's thesis on using code graphs to provide structured context for AI-assisted software engineering in Ericsson's Radio Baseband L1 codebase. The work includes surveying research, identifying relevant code entities and relationships, implementing source-code graph extraction, defining context effectiveness measures, and evaluating code graphs against parsing and retrieval alternatives. The thesis will also recommend methods for maintaining context freshness and consistency.

Conduct a master's thesis investigating AI and agentic AI methods for automating ASIC verification debug. Analyze simulation logs, waveforms, assertions, coverage data, test results, and design metadata to identify failure root causes. Compare prompt workflows, tool invocation, iterative reasoning, and specialized agents against conventional or simpler AI baselines. Develop an evaluation methodology assessing accuracy, speed, efficiency, robustness, and practical usefulness, then document findings and recommendations.

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.