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 |
| AI Software Engineer Intern Internship role focused on applied research and productization of Vision-Language Models (VLM) and Vision-Language-Action (VLA) models, including pre-training, fine-tuning, alignment, data pipelines, fusion strategies, action components, and model optimization for efficient deployment on Intel hardware. The role involves evaluating models and potentially publishing results. |
| Post-trainData |
| 9 |
| Machine Learning Engineer Machine Learning Engineer/Data Scientist role focused on agent harness research and model fine-tuning, involving building evaluation benchmarks, iterating on agent harness components (context, memory, tools, skills), developing and maintaining post-training pipelines, designing RL environments and reward functions, and optimizing training runs. The role emphasizes the intersection of research and engineering for agentic applications. | Post-trainAgent | 8 |
| Data Science Student for AI Solutions Group Intel's AI Solutions Group is seeking an MSc/PhD student to work on state-of-the-art AI capabilities for chip development. The role involves solving high-value problems using ML, DL, and LLMs, from ideation and research to preparing solutions for deployment. Requires strong Python, ML/DL knowledge, and familiarity with AI tools like PyTorch or Scikit-learn. | Post-train | 8 |
| Applied Machine Learning Engineer (LLMs & RL) Applied Machine Learning Engineer focused on fine-tuning large language models (LLMs) and Reinforcement Learning (RL). Responsibilities include designing and maintaining post-training pipelines, developing RL environments and reward models, debugging and scaling distributed training, and designing experiments and evaluation metrics. | Post-trainAgent | 8 |
| Senior Principal Engineer – AI Applied Research Senior Principal Engineer in AI Applied Research at Intel, focusing on applying AI/ML to logic IP design and semiconductor manufacturing. The role involves conducting applied research, developing proof-of-concept models, and implementing solutions to demonstrate business value, requiring expertise in deep learning, ML, RL, NLP, GNNs, and time-series. The position emphasizes leadership, influencing partners, and mentoring technical leaders. | Post-train | 8 |
| AI Software Engineering Intern AI Software Engineering Intern at Intel in Poland. Responsibilities include collaborating on AI algorithm development, optimizing and fine-tuning AI models, conducting applied research, supporting hardware-software integration, and contributing to system-level deployment of AI solutions across computer vision, machine learning, and deep learning domains. | Post-trainServe | 7 |
| 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 |
| Software Solutions Engineering Intern Internship role focused on the research and application of Vision-Language-Action (VLA) algorithms in robot scenarios. Responsibilities include VLA data collection, model fine-tuning, performance testing, problem analysis, and optimization using Python and frameworks like lerobot, PyTorch, and TensorFlow. The role involves improving model adaptability and execution accuracy for robot systems. | Post-trainAgent | 7 |
| AI Software Engineering Intern AI Software Engineering Intern at Intel contributing to the design, development, and optimization of AI software solutions across computer vision, machine learning, and deep learning. Responsibilities include implementing and tuning models, conducting applied research, and assisting with system-level deployment. | Post-train | 7 |