Your Role: Shaping the Future of AI Technology
Are you passionate about AI and looking for a role that intertwines state-of-the-art hardware and software? Intel's NPU IP is at the heart of our AI PC, representing a critical component of our cutting-edge products and unlocking the societal benefits that AI will bring. Our products are built on power-efficient silicon and an optimized software stack, but our success is built on people like you.
We're looking for someone who is eager to dive into the world of AI, supporting pre-silicon HW and SW stack validation and post-silicon SW stack optimization. If you are a software engineer with a HW design or validation background, this could be an ideal opportunity to explore the Intel NPU HW/SW Co-Design ecosystem.
Key Responsibilities:
As an AI Embedded Software Engineer, you'll be an integral part of a dynamic team developing NPU IP Pre-Silicon Simulation software models.
Collaborate with multi-disciplinary engineers and architects to model future Intel NPU hardware IP, crafting software virtual platforms for early software bring-up and robust hardware validation environments.
Gain a broad understanding of how HW-based acceleration products are built and learn why these products are the real engine behind the AI revolution.
What Awaits You on Your Intel Journey:
Innovative Environment: Immerse yourself in cutting-edge virtual platform modelling technology, using platforms such as Intel Simics and state-of-the-art UVM hardware validation methodologies.
Rapid Skill Enhancement: Expand your existing expertise through advanced software engineering techniques and embedded software development practices.
Collaborative Excellence: Work alongside RTL designers, validation engineers, and SW/FW and OS driver developers to deliver world-class products
Architectural Influence: Grow your AI development skills and contribute to architectural and technical deliverables while adhering to sound software engineering principles.
Career Growth: We will invest in you, helping you to sustain and reach your long-term career goals focusing both on hard and soft skill development.
Minimum Qualifications:
Master/Bachelor of Science in Computer Science, Electrical Engineering, or relevant technology degree/qualification with 3+ years of applicable industry experience.
Software Proficiency: Strong background in object-oriented programming, C++.
Linux Software Development: Development and debug experience is a must.
AI Fundamentals: Basic understanding of underlying principles such as dot product (multiply and accumulate), activation functions, convolution, etc., and how they relate to, and enable, AI network topologies.
Experience with Python, Git for source code management and CI/CD and automated software/hardware regression testing are highly advantageous.
Familiarity with SoC Architecture: System-level understanding of data flows and memory management, including simulation of HW components and functions such as registers, data/memory interfaces, MMUs, CPUs, DSPs, NoCs, interrupts, and CPR (clock, power, reset).
Preferred Qualifications:
Embedded Hardware Design: Experience with VHDL/Verilog/SystemVerilog for simulation and synthesis is highly advantageous.
Virtual Platform Modelling: Hands-on experience with Intel Simics or similar virtual platform modelling and simulation environments.
Multithreaded Application Development: Expertise in C/C++.
Experience with UVM: For hardware verification.
Hardware Validation: experience with SystemVerilog and UVM for pre-silicon hardware validation
Embedded SW, Firmware, and/or System Validation: Debug and signoff experience.
Numerics and AI Data Processing: Understanding of floating point datatypes, type conversion, commutativity, and precision in the context of AI data processing structures such as tensors and blobs.
Additional Information:
Requirements listed would be obtained through a combination of industry-relevant job experience, internship experiences, and/or schoolwork/classes/research. On-the-job training will be given in these areas as you take the next step in your career with our team.
Work Model for this Role
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.