Intel

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.

Image Processing Engineer with C++/Linux experience to develop and implement computer vision algorithms for nanometer-scale metrology applications in mask and semiconductor manufacturing. The role involves algorithm development, programming, software tool development, testing, documentation, and user interaction to improve quality control and process development.

Product Manager for AI Compute Software, focusing on performance-critical middleware for AI training and inference on accelerators and CPUs. The role involves defining product strategy, roadmap, and execution, collaborating with hardware, framework, and system software teams to ensure high performance, scalability, and developer usability.

Sr. Security Architect role focused on applying AI-driven tools to enhance security architecture for Client and Data Center SoCs, including firmware and low-level hardware/software. The role involves using AI for vulnerability identification, code analysis, threat modeling, and defining security specifications, aiming to discover risks earlier and more broadly than traditional methods.

Software Development Engineer focused on optimizing Neural Network performance for Intel AI accelerators using compiler technologies and graph theory. The role involves driving design, implementing compilation passes, and developing performance analysis tools for future AI hardware.

AI Frameworks Engineer focused on optimizing generative AI models for efficient inference using the OpenVINO toolkit across Intel hardware, from edge to cloud. This role involves deep dives into generative model architectures and the OpenVINO ecosystem, implementing new features, and optimizing performance for state-of-the-art inference solutions.

Senior AI SoC Architect role at Intel focused on architecting next-generation datacenter AI SoCs and rack-scale AI servers. Responsibilities include defining and leading architecture development, influencing direction, and collaborating across disciplines for optimized power/performance. Requires 10+ years of SoC architecture experience.

Senior Design Verification Engineer for Intel's Neuromorphic Computing Lab, focusing on pre-silicon verification of novel AI accelerator architectures. The role involves developing a scalable verification framework, writing directed and random tests, debugging, and using AI tools to improve productivity. Experience with UVM/OVM and AI tools for test generation is required.

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.

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 development engineer to work on oneDNN project, a complex cross-platform open-source software project focusing on neural network performance. oneDNN is a critical component of Intel AI strategy, powering key AI applications. Role involves design, development, and maintenance of new functionality in oneDNN to enable performance critical portions of AI workloads, supporting software developers optimizing AI frameworks and workloads for Intel CPUs and GPUs.

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.

Senior Director to lead Enterprise Data & AI Enablement, reporting to VP of AI and Data. Drives strategic roadmap for data and AI capabilities, focusing on robust data foundations for advanced AI applications. Leads cross-functional teams, collaborates with AI leadership, and influences enterprise-wide data and AI strategy. Responsibilities include defining data strategy, overseeing data ingestion and engineering, enabling AI/ML with tooling and environments, developing knowledge products, integrating structured/unstructured data, and designing data models for BI and AI workloads. Also responsible for data governance, quality, literacy, and compliance. Requires proven experience with large-scale data platforms, enterprise applications, data architecture, warehousing, lakehouse technologies, and building AI-ready data foundations. Must demonstrate ability to drive enterprise-wide data strategy, influence senior leadership, build and scale data teams, and partner with AI/ML teams. Experience in regulated industries is preferred.

This role is for an End-to-End GPU AI Software Architect at Intel, focusing on the entire software stack from firmware to applications to ensure Intel GPU AI software meets product requirements for workloads, performance, and stability. The architect will make key technical design decisions, influence technical direction across the industry, and mentor other technical leaders.

Seeking a Verification Team Leader for Intel's AI group in Israel to manage a team, develop verification plans, oversee verification environments, and collaborate with design teams for cutting-edge AI hardware products. Requires 10+ years in VLSI chip verification, 4+ years in leadership, and experience with SoCs and AI applications.

Sales Development Manager for Intel, focusing on driving adoption of Intel-based AWS instances for AI and enterprise workloads. The role involves strategic partnerships, executive influence, and providing market feedback to shape product roadmaps. While the company and its products are AI-focused, the role itself is sales-oriented.

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.

This role focuses on building and scaling an ecosystem of Solution Integrators (SIs) to drive the adoption and deployment of Edge AI systems in the education segment across Southeast Asia. The specialist will design the channel engine, recruit and enable SIs, and collaborate with partners to create repeatable reference architectures and bundled solutions. While not coding, the role requires understanding Edge AI complexities to advise partners.

Student/Intern role focused on DevOps and Infrastructure Engineering, with exposure to AI tools and technologies. The role involves hands-on development in Python for various DevOps environments (GitHub, Jenkins, K8s, Azure Cloud) and exploration of other programming languages like JavaScript, TypeScript, and Node.js. While AI is mentioned as a tool to enhance work, the core responsibilities are in DevOps and infrastructure.

This role focuses on yield analysis and improvement in advanced packaging technology and manufacturing. The engineer will extract insights from large datasets using statistical methods and machine learning techniques, develop solutions to manufacturing process problems, and influence the yield improvement roadmap. The role requires understanding the relationship between electrical and physical fails, inline defect metrology, and collaborating with various engineering teams.

Student role focused on tactical planning, cost savings, efficiency, process improvements, analysis, budget control, and procurement management within Intel's Client Validation Engineering organization. Requires economics, finance, or related studies, with AI tool usage and supply chain experience being advantageous.

Software Enabling and Optimization Engineer role focused on optimizing software for Intel products, including AI frameworks, across various domains like Cloud, AI, HPC, Gaming, Graphics, and Edge computing. Responsibilities include development, integration, testing, debugging, and optimization of software, collaborating with customers and partners, evangelizing Intel's tools, and researching innovative solutions. Familiarity with AI frameworks and performance optimization is preferred.

The Yield Platform Analyst role at Intel focuses on driving yield improvement across advanced packaging technologies. This involves defining goals, establishing relationships between material/tool/process modulators and yield, performing statistical analysis, and extracting insights from data using machine learning and coding techniques. The candidate will develop systems to transform data into yield improvement actions and ensure manufacturability. This role requires defining roadmaps, influencing strategies, and working with cross-functional teams throughout the technology lifecycle from pathfinding to HVM ramp.

This role focuses on debugging and resolving complex system-level issues for Intel's AI GPU product roadmap, involving hardware, software, firmware, and silicon components. The engineer will lead root-cause analysis, manage the bug lifecycle, and collaborate with cross-functional teams to ensure efficient resolution of platform issues and customer escalations. While familiarity with ML frameworks and AI/ML deployment debugging is a plus, the core responsibility is system-level engineering and debugging.

This role focuses on yield enhancement in semiconductor manufacturing by applying statistical analysis, machine learning, and data analytics to identify root causes of yield limiters and optimize manufacturing processes. The engineer will extract insights from diverse data sources, develop tools for high-volume data analysis, and collaborate with cross-functional teams to drive process improvements and ensure product quality.

This role focuses on yield improvement in semiconductor manufacturing by applying statistical analysis, machine learning, and coding techniques to analyze big data from manufacturing processes, identify root causes of defects, and develop data-driven strategies for yield optimization. The engineer will develop systems and methodologies for data consolidation, perform statistical analysis and visualization, and transform data into actionable yield improvement strategies.

Internship role focused on IP block design, supporting development flows, tools, and methodologies within Intel's Silicon and Platform Engineering Group. Requires Python, Git, CI/CD, SQL, and experience using AI coding tools with critical evaluation of their output. Preferred qualifications include web development, authentication, and AI agent familiarity.

Intel's Health and Life Sciences (HLS) vertical is seeking a Roadmap and Solutions Manager to define and align strategic roadmaps for intelligent, secure, and reliable medical devices and life sciences instruments. The role involves translating market needs, customer insights, and regulatory considerations into actionable roadmaps and deployable solutions, with a focus on edge-native solutions. The candidate will bridge market requirements and internal execution, ensuring solutions are grounded in real-world deployment constraints and feedback is incorporated into roadmap evolution. Familiarity with AI/ML in healthcare is preferred.

AI Software Development Engineer at Intel focused on developing content and datasets for AI-based graphics and next-generation rendering technologies like Super Resolution and Frame Generation. The role involves building scalable workflows for generating scenes, effects, and dataset content using AI tools and procedural methods, working closely with AI and graphics engineers.

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 role focuses on the pre-silicon verification of NPU AI accelerator products, involving the development of verification environments, test plans, and test cases using System Verilog Assertions (SVA) and formal verification methodologies. The primary deliverable is the validated design of AI accelerator components before they are manufactured.

Internship role focused on building AI software stacks, GPU programming, and performance optimization. Contributes to design, development, and optimization of AI software solutions, algorithms, frameworks, and architectures. Assists in implementing and tuning models for performance and accuracy, applied research, and hardware-software integration. May involve creating AI software solutions and system-level deployment for scalable and efficient AI.

Student role focused on supporting the adoption of Intel's Design Generative AI tools through communication, community building, training, and feedback collection. The role involves user research, go-to-market execution, community management, and creating enablement assets to drive product adoption and gather user insights.

Software Engineer role focused on designing, developing, testing, and debugging software tools, flows, and methodologies for hardware design automation within the semiconductor industry. The role involves capturing requirements, writing functional and test code, automating build/deployment, and performing testing. It also includes designing web interfaces for tool configuration and control, and supporting Linux EDA tool infrastructure. While AI is mentioned as a general company goal, the core responsibilities are in software engineering for design automation, not direct AI/ML model development.

Internship role focused on SoC integration and verification, with an emphasis on learning and applying RTL/logic development, functional verification methodologies, and utilizing AI tools for automation. The role involves debugging, simulation, and collaboration within a hybrid work model.

Internship role supporting the design and development of integrated AI solutions combining software, hardware awareness, and system-level concepts. Focus on learning AI systems development across the tech stack, from models to platform considerations, and contributing to prototyping and testing.

This intern role focuses on the hardware engineering aspects of AI ecosystem solutions, involving algorithm and framework design, AI software architecture, and optimizing AI solutions for hardware performance. It combines hardware engineering with AI/ML techniques for design efficiency and analysis, including implementing and tuning models, applied research, and system-level deployment. The role emphasizes AI augmenting engineering judgment.

Student role in a semiconductor manufacturing environment focused on data science and automation. Responsibilities include supporting daily operations, identifying and automating manual bottlenecks, and building AI-driven solutions for data analysis and predictive methodologies. Requires strong Python and SQL skills, analytical abilities, and willingness to learn manufacturing processes.

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.

Software Development Intern role focused on AI-enhanced requirements engineering within Intel's Data Center Requirements team. The intern will contribute to intelligent automation, ML-driven data analysis, and AI-powered tool creation, leveraging web development, scripting, database, and data structure skills. The role emphasizes learning software development methodologies, debugging, automation, and data analysis.

Seeking an AI Tools Development Intern to support the design, development, and validation of AI tools, working closely with experienced engineers. This role involves hardware design activities, documentation, and collaboration with cross-functional teams. The intern will gain practical experience in hardware design processes and engineering tools.

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.

Manager for VMaaS and CaaS Platforms, responsible for end-to-end ownership, reliability, and evolution of Intel's VMaaS and CaaS platforms across Enterprise IT and Labs. This role ensures stable operations, scalable architecture, and disciplined lifecycle management, while leading the transition through platform modernization, EOL migrations, and AI and automation driven operations. The role also involves people leadership, stakeholder management, and driving the adoption of AI and automation tools to improve operational efficiency.

Internship role focused on supporting the development and optimization of integrated AI solutions, collaborating with hardware and software teams to meet business and customer needs. Involves performance benchmarking, data analysis, and applying AI frameworks to refine solutions for AI use cases.

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.

This role focuses on data analysis and developing AI/ML techniques for manufacturing processes within Intel Foundry. The primary responsibilities include developing data acquisition and analysis scripts, creating visualization dashboards, and exploring foundational AI/ML to improve pattern detection and automate analyses in manufacturing data. The role requires foundational understanding of AI/ML concepts and experience with data analysis tools and programming languages.