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.

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.

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 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.

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.

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.

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.

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.

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.

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.

Intern role responsible for verifying architectural functional blocks of IP or SOC, including creating test cases and test benches using UVM methodology. Develop pre-silicon validation tests to ensure systems meet design requirements. Perform RTL and GLS simulation, create RTL validation test plans, run system simulations, and resolve failed tests. Build infrastructure for regressions and volume validation. Document test plans across platforms (IP library, Complex-IPs, Subsystems). Contribute to verification methodology and infrastructure. Adopt and implement industry-standard verification tools and methodologies (Formal, Low Power, Performance, Co-Simulation).

Supports management/senior leadership to incorporate process and quality improvements in Intel's substrates strategy. Defines material inspection methodology, conducts studies related to cost control, process control, and production yield, and implements plans and programs to optimize supply chain. Supports product long range plan development by defining next generation methodology capabilities to support Intel's supply chain roadmap. Explores and benchmarks emerging technology in the industry. Contributes to Intel's future technology definition and requirements. Highlights gaps between roadmap strategy, manufacturing capability, and market demands and recommends solutions to addresses those gaps. Tracks supply demand trends, conducts root cause analysis to find opportunities for process and quality improvements, and collaborates with supply chain leads to implement solutions. Leads supplier selections for new business in partnership with commodity managers and technical/quality partners and drives product and purchase specification content to ensure commodity performance compliance. Performs alternate sourcing risk mitigation for single sourced commodities. Establishes control standards, determines KPIs, monitors performance against targets, and drives root cause analysis for supply chain issues to arrive at solutions. Drives supplier process window validation activities on critical process modules through all stages of development. Drives supplier improvements on quality, reliability, yield, and cost. Maintains quality standards and systems, creating relevant specifications to minimize variability and subjectivity to align with operational capability requirements. Leads quality excursion management and drives failure mode analysis with suppliers.

Project Controls Engineer at Intel Foundry Construction Sourcing responsible for cost/estimating/schedule controls for semiconductor manufacturing factory projects. This role involves cost reporting, forecast development, leading estimate development, driving process improvements, financial updates, cost reduction strategies, and partnering with procurement on commercial activities. Requires experience in estimation, cost control, capital, OpEx/Spending, and FPnA.

Internship role focused on firmware development for Intel silicon products, involving design, development, validation, and debugging of embedded software for domains like BIOS, microcontrollers, and memory systems. Responsibilities include system-level modeling, algorithm development, and hardware-software integration, often under constraints. Collaboration with architects and engineers is expected. The role is for graduate students with strong programming skills (C++, C, Assemble) and experience in firmware or embedded software development.

Intern role focused on Xeon IO performance engineering, involving validation, analysis of KPIs, debugging, and optimization of networks for Intel's AI performance across diverse product segments. Responsibilities include executing performance validation, identifying bottlenecks, supporting customer co-validation, and mitigating single-point-of-failure risks in I/O domains.

Internship role focused on developing, validating, and debugging embedded software and firmware for Intel's technology platforms, involving system-level challenges and collaboration with engineers. Responsibilities include assisting in design, debugging, validation, code reviews, and scripting.

This is an internship role for a Design Verification Engineer focused on verifying the functional logic of silicon designs, ensuring alignment with architecture specifications. Responsibilities include developing verification plans, test benches, and environments, performing emulation and simulation, and debugging design issues. The role requires proficiency in SystemVerilog/Verilog and understanding of verification methodologies like OVM/UVM.

System Firmware Engineer responsible for developing, maintaining, and optimizing reusable components for seamless integration across Intel's client technology ecosystem. This role involves partnering with customers and vendors, establishing architecture standards, researching and prototyping firmware, evangelizing tools, and driving product improvements. Requires expertise in system firmware, software debug, and low-level software engineering.