Currently tracking 56 active AI roles, down 34% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $122k–$414k (avg $253k).
Intel currently has 84 active job listings related to artificial intelligence. The majority of these roles, 51%, are focused on serving infrastructure, with agents representing another significant portion at 24%. Engineering is the most frequent function for these positions. The company is actively hiring in the United States, China, and Mexico. Frequent technical tags include model serving, inference infrastructure, and agent orchestration. In the last 30 days, Intel has added 73 new AI roles, representing a 52% increase compared to the previous 30-day period.
Intel currently has 59 active AI-related roles in our index. The most common open titles are: AI Software Engineering Intern (3), AI Software Engineer Intern (2), GenAI Software Solutions Engineer (2), Graduate Talent (GenAI Software Solutions Engineer) (2), AI Algorithm Engineer. Most positions are in Engineering and Research.
Intel's active AI hiring is concentrated in: serving infrastructure (49%), agents (29%), application (8%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Intel is hiring AI talent in: United States (28 roles), China (7 roles), Mexico (6 roles), Malaysia (6 roles).
Job postings at Intel most frequently reference: model serving, inference infra, agent orchestration, rag, tool use.
In the past 30 days, Intel has posted 28 new AI-related roles. That is a -63% change versus the prior 30 days (75 → 28).
| Title | Stage | AI score |
|---|---|---|
| AI Research and Development Engineer (Physical AI) This role focuses on building the end-to-end stack for robotic intelligence, bridging high-level research and low-level performance optimization for physical AI. It involves training large-scale Vision-Language-Action (VLA) models and optimizing them for real-time deployment on edge hardware, including developing safety runtimes and model-agnostic inference APIs. | Post-trainServe | 9 |
| Neuromorphic Applications Researcher- Temporary Position Research role focused on developing and benchmarking AI algorithms and robotics applications for Intel's next-generation neuromorphic architecture, aiming to enable physical AI systems with groundbreaking performance and efficiency. The role involves evaluating applications on neuromorphic hardware, validating the SDK, and publishing results. |
| ShipServe |
| 9 |
| AI Algorithm Research Intern – Neuromorphic Computing AI Algorithm Research Intern focused on developing, implementing, and benchmarking algorithms for Intel's next-generation neuromorphic architecture to enable applications in edge computing, signal processing, and autonomous systems. The role involves contributing to Intel's neuromorphic SDK and publishing research findings. | Data | 9 |
| AI Research Engineer/Scientist (OpenVINO, NNCF) AI Research Engineer/Scientist to drive the development of the Neural Network Compression Framework (NNCF), focusing on research and development of SOTA compression algorithms for high-performance neural network inference optimization within the OpenVINO ecosystem. | Post-trainServe | 7 |
| Robotics Research Intern Robotics Research Intern at Intel focusing on advanced algorithmic development and robotics research for next-generation robotic technologies. The role involves researching, designing, and optimizing robotics algorithms, control systems, and AI/ML models, with a focus on enabling intelligent autonomous systems and innovative robotic applications. Collaboration with cross-functional teams to translate research into practical implementations is key. | Agent | 7 |
| Systems Research Engineer/Scientist Systems Research Engineer/Scientist role focused on leveraging AI/ML for higher efficiency and performance in system architecture innovations, including high-performance cluster computing, virtualization, and accelerated computing. The role involves prototyping, characterizing, and analyzing workloads, developing tools for performance assessment, and influencing future product roadmaps. Requires strong systems knowledge and hands-on experience with AI workloads, with a focus on performance modeling and analysis of AI inference or training. | Serve | 7 |