Intel
- HQ
- Santa Clara, US
- Founded
- 1968
- Size
- 120,000+
- Website
- intel.com
Currently tracking 56 active AI roles, down 27% 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 |
|---|---|---|
| Chip Design Team Lead - AI SOC Lead a digital design team developing cutting-edge AI SoCs, focusing on RTL coding, PPA analysis, and cross-functional collaboration for high-end chip design. | Serve | 7 |
| Deep Learning System Validation Engineer This role focuses on validating and developing hardware structures and interfaces to accelerate deep learning hardware and software performance for AI systems. It involves developing test plans, leading pre- and post-silicon activities, and collaborating with product and design teams to define next-generation requirements and influence the AI product roadmap. The work impacts AI solutions in both on-device and data center deployments. | Serve | 5 |