Intel

This role focuses on building and optimizing a next-generation LLM inference system, including model optimization, inference runtime, and system-level design. It involves research and engineering to implement and optimize core techniques across the stack from model to kernels to runtime to distributed systems, with a key focus on GPU kernel and runtime optimization for an end-to-end AI rack software system for LLM inference.

GenAI Software Architect role focused on building and optimizing machine learning products and solutions, particularly LLM-based systems and AI agents. Requires deep expertise in GenAI algorithms, solution architecture, performance tuning, and experience with frameworks like LangChain, RAG pipelines, and vector databases. The role involves developing custom AI tools and optimizing GenAI workloads for edge devices.

This intern role focuses on AI agent development, including designing autonomous agents, integrating tools and APIs, building RAG systems, orchestrating multi-agent collaboration, and implementing performance monitoring. It requires familiarity with agent frameworks like LangChain and an understanding of LLM architectures, prompt engineering, and RAG techniques. The role also involves traditional firmware validation tasks like test case development and issue investigation.

Senior GenAI Software Architect role focused on building and architecting machine learning products and solutions, with a strong emphasis on GenAI algorithms, LLM-based systems, and AI agent development. The role involves translating ML models into software, optimizing for edge devices, and supporting customer/partner deployments.

Develops and integrates large models (LLMs/VLMs/VLAs) into ROS 2-based robotic systems for perception, planning, and execution. Designs reward functions, training curricula, and evaluation protocols for embodied tasks, with a focus on training RL policies for manipulation.

Senior GenAI Software Architect role focused on building and architecting machine learning products and solutions, with a strong emphasis on GenAI algorithms, LLM-based systems, and AI agent development. The role involves translating ML models into software, optimizing for edge devices, and supporting customer/partner deployments.

Develop Intel Neural Compressor product and related tools, optimize for Intel AI platform (CPU, GPU, AI Accelerator). Research and implement quantization and compression techniques for LLMs and text-to-image/video generation models. Track and explore cutting-edge directions in efficient model deployment and inference/finetuning acceleration.

The Physical AI Engineer role at Intel focuses on designing and developing integrated AI solutions for deep learning and machine learning systems, encompassing hardware, software, firmware, and silicon. The role involves AI systems architecture, defining product specifications, and impacting the AI product roadmap. Key responsibilities include developing new methods in areas like reinforcement learning, computer vision, and robotics, leading design and implementation of AI systems, and delivering end-to-end technical solutions for customer problems. The role also involves analyzing AI infrastructure reliability and collaborating on next-generation requirements.

GenAI Software Architect role at Intel, focusing on building and optimizing AI/ML-based products and solutions, particularly LLM-based systems and AI agents. Requires expertise in GenAI algorithms, solution architecture, performance tuning, and experience with frameworks like LangChain and RAG pipelines. The role involves developing and deploying machine learning models and methods into software, with a focus on real-world use cases and edge device optimization.

This role focuses on building AI agents that automate security engineering tasks, including CVE triage, security advisory drafting, and SDL automation, by leveraging LLMs and agent frameworks.

This role focuses on optimizing AI software solutions for Intel's AI PC environments by collaborating with customers and ecosystem partners. The engineer will develop, integrate, test, tune, and debug software, leveraging tools like OpenVINO, Llama.CPP, Ollama, LMStudio, and vLLM, to enhance product adoption and differentiation. Key responsibilities include researching and prototyping software, evangelizing Intel's tools, leading pre-enabling efforts, and identifying key workloads for future product designs.

Develop and optimize high-performance software modules using Python/C/C++ with AI technologies, including LLMs and VLMs within agentic frameworks, and optimize media drivers for Intel platforms.

AI Software Engineering Intern role focused on designing, developing, and optimizing AI algorithms and frameworks, with contributions to implementation, tuning, applied research, and prototyping for scalable AI solutions. The role involves working with computer vision, machine learning, and deep learning, and requires programming ability in Python and familiarity with ML frameworks.

GPU Software Engineer focused on AI-driven software development and validation, building and optimizing software quality measurement and tracking systems. Responsibilities include developing high-performance software modules with AI technologies and models, optimizing media drivers, and deploying LLMs/VLMs within agentic frameworks.

Internship role focused on optimizing AI software solutions, including algorithms, frameworks, and architectures for computer vision, machine learning, and deep learning. Responsibilities include researching model quantization and graph transformation, evaluating LLM performance on Intel platforms, analyzing software bottlenecks, and assisting in implementing and tuning AI models for performance and accuracy. The role emphasizes hardware-software integration and collaboration for scalable AI solutions.

This internship focuses on optimizing core GPU compute kernels for AI and numerical workloads, validating GPU IP with AI inference and training workloads, and performing GPU performance profiling and analysis. The role involves hardware/software codesign for next-generation Intel GPU and AI accelerator platforms.

Intern role focused on optimizing GPU compute kernels for AI workloads and validating GPU IP. Involves performance profiling, analysis, and modeling to improve next-generation Intel GPU and AI accelerator platforms.

This internship focuses on optimizing core GPU compute kernels for AI and numerical workloads, validating GPU IP with AI inference and training workloads, and performing GPU performance profiling and analysis. The role involves hardware/software codesign for next-generation Intel GPU and AI accelerator platforms.

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.

Intern role focused on optimizing CPU kernels for AI workloads, including LLMs and multimodal models, using Intel architecture features and performance profiling tools. Integrates custom operators into production frameworks.

Internship role focused on developing efficient algorithm solutions for accelerating large AI models and agentic systems, with an emphasis on deployment in resource-constrained computing platforms.

AI Compiler and Library Engineer Intern at Intel, contributing to the design, development, and optimization of AI software solutions, including algorithms, frameworks, and architectures. Focuses on implementing and tuning models for performance and accuracy, applied research, and hardware-software integration, with potential involvement in system-level deployment. The role emphasizes learning and skill development through hands-on projects supporting Intel's business goals.

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.

AI Software Engineering Intern focused on designing, developing, and optimizing AI software solutions, including algorithms, frameworks, and architectures. Key responsibilities include tuning deep learning models, exploring model compression techniques (quantization, pruning), and conducting applied research for system-level deployment and hardware integration. The role emphasizes practical engineering applications and inference optimization.

AI Software Engineer Intern role focused on the design, development, and optimization of AI software solutions, including algorithms, frameworks, and architectures. Responsibilities include implementing and tuning models, applied research, hardware-software integration, and system-level deployment. The role involves learning and applying knowledge in areas like computer vision, machine learning, and deep learning, with a focus on performance and accuracy.

This intern role focuses on optimizing deep learning models and their deployment for Intel GPUs/CPUs. Responsibilities include performance tuning, debugging accuracy and memory issues, developing deployment frameworks (e.g., using vLLM), and creating high-performance kernels. The role involves technical syncs with architects and transforming innovative ideas into production-ready features.

Research intern position focused on Confidential AI systems and Agent-CC solutions for hyperscale, involving LLMs, AI systems, and microarchitecture. Requires programming, foundational computer architecture, and AI math skills.

AI Software Engineering Graduate Intern to contribute to the development and optimization of AI workload solutions spanning algorithms, AI software frameworks, system software, and infrastructure. Responsibilities include reproducing AI inference workloads, building workload profiles, identifying system bottlenecks, and performing performance analysis to support hardware/software co design for next generation AI SoC products.

Intel CAIGC is seeking an AI Framework Engineer to advance AI technologies and software ecosystems, focusing on enabling the AI PC ecosystem and delivering full-stack GPU IP solutions. The role involves research, validation, performance evaluation, and optimization of AI models and frameworks on Intel platforms.

This is a graduate intern position in technical sales focused on providing technical expertise, designing solutions, and engaging with customers to drive the adoption of Intel technologies. The role involves building foundational technical and sales skills, developing demonstrations, and documenting best practices. While familiarity with AI frameworks and fundamentals is required, the core function is technical sales support, not direct AI/ML model development or deployment.

Software Engineer role at Intel focused on building the AI PC ecosystem and full-stack GPU IP. The role involves collaborating with OS vendors and ISVs to enable differentiated AI experiences, focusing on NPU IP and GPU IP across Intel's product portfolio. The mission is to reshape end-user experiences with AI and drive high-performance computing with GPUs.

Intern role focused on optimizing GPU compute kernels for AI workloads and validating GPU IP. Involves performance profiling, analysis, and building performance models to understand architecture-level behavior, contributing to hardware/software codesign for next-generation Intel GPUs and AI accelerators.

Research intern focusing on system reliability (RAS) and silent data error characterization and mitigation for AI and general-purpose compute platforms, including heterogeneous systems and large-scale server clusters. Responsibilities include designing and running experiments, analyzing logs, and prototyping detection/diagnosis methods to improve data integrity and platform robustness across the HW/FW/OS/runtime stack.

This internship focuses on supporting the design, deployment, and troubleshooting of Cloud and AI systems and solutions, collaborating with hardware and software teams to optimize for real-world use cases. The role involves applying AI framework knowledge and systems engineering principles to ensure reliability and scalability.

Intern role assisting Platform Validation Engineers with test case creation, automation scripting, and platform validation. The role involves developing AI solutions to improve script automation, execution, and debugging, ultimately supporting the quality of Intel Xeon products.

AI Performance Engineer Intern at Intel focused on analyzing silicon chip performance for deep learning, conducting large-scale benchmarks, designing automation tools for data collection and analysis, and researching new architectural features for GPUs, CPUs, and SoCs. The role involves system-level modeling, testing, characterization, and performance-per-watt analysis, with a strong emphasis on understanding deep learning models and frameworks.

This is an intern role focused on software validation for datacenter products, with a specific mention of using AI-assisted approaches to improve validation processes. The core function is software validation and testing, not direct AI model development or deployment.

Research Intern focusing on system innovation, cost optimization, and GPU interconnect protocols for disaggregated AI supernode architectures. The role involves exploring architectural innovations, implementing distributed memory pooling, and researching Ethernet-native GPU interconnect protocols for large-scale AI inference and training clusters. Familiarity with RDMA, Mellanox tools, and LLM inference benchmarking methodologies is required.

Internship role focused on the design, development, and optimization of AI software solutions, including algorithms, frameworks, and architectures. The role involves implementing and tuning models for performance, applied research, and hardware-software integration, with potential for system-level deployment. Familiarity with PyTorch, model profiling, and optimization is a plus.

Internship role focused on the design, development, and optimization of AI software solutions, including algorithms, frameworks, and architectures. The role involves implementing and tuning models for performance, applied research, and hardware-software integration, with potential for system-level deployment. Familiarity with PyTorch, model profiling, and optimization is a plus.

This role focuses on optimizing web runtime performance for Intel AI PCs by enabling and optimizing key Chromium components, including Web AI features, on Intel hardware (CPU, GPU, NPU). The engineer will work with internal hardware teams and the Chromium open-source community.

Cloud Software Development Engineer at Intel, focusing on optimizing software stacks for Intel hardware in cloud environments. Specializations include data services, AI/ML, or open-source development. Responsibilities involve designing, developing, validating, and debugging software solutions, with a focus on performance optimization and customer support.

AI Marketing Intern role focused on developing an Education Edge AI playbook, analyzing AI use cases, and proposing features for the AI Suite roadmap. Requires strong communication, program management, and AI-related experience.

Intern role contributing to system software design, development, and validation across firmware, drivers, OS, and middleware for Intel platforms. Focuses on cross-stack optimization and reference platform development. Requires Master's candidates in CS, CE, or EE with Python/C/C++ experience and knowledge of SW development/testing processes.

Internship role focused on firmware development for embedded systems like BIOS, microcontrollers, and memory systems, involving design, development, validation, and debugging. Requires proficiency in C/C++/Python and foundational knowledge of embedded software and computer architecture.

Intern role focused on developing middleware software solutions that connect applications and hardware, enhancing communication, data management, and system efficiency on Intel's platforms. Responsibilities include API design, protocol implementation, performance tuning, debugging, and applying Agile methodologies.

Intern role contributing to the design, development, and validation of system software across various layers of the software stack, including firmware, drivers, operating systems, and middleware, to enable Intel platforms and technologies. Focuses on cross-stack software optimization and reference platform development.

Internship role focused on designing, developing, validating, and debugging embedded software solutions for Intel's hardware. Responsibilities include system-level modeling, algorithm development, hardware-software integration, and bug analysis in constrained environments.