We are looking for an experienced AI Software Development Engineer to drive end-to-end optimization of AI inference workloads on Intel GPUs. This is a vertical workload optimization role spanning graph compilation, runtime execution, and low-level GPU kernels, delivering measurable performance improvements for modern AI models.

Key Responsibilities

- Optimize emerging AI inference workloads such as Large Language Models (LLMs) and Diffusion models on GPUs

- Develop and optimize graph-based compilation flows (e.g., MLIR/LLVM) for neural network workloads

- Write and tune performance-critical GPU kernels and runtime code in C or parallel programming languages

- Identify and resolve bottlenecks across compiler, runtime, and kernel layers

- Profile, benchmark, and characterize AI workloads to validate performance gains

- Collaborate with hardware, driver, and framework teams on hardware/software co-optimization

What We're Looking for Professional traits:

- Excellent problem-solving abilities and strong attention to detail

Qualifications

Minimum Requirements - Bachelor's degree with 4 years of relevant experience, OR Master's degree with 2 years of relevant experience in Computer Science or a related field

The experience must include:

- Strong C development and debugging skills

- Solid understanding of GPU architectures or AI accelerators

- Hands-on experience with modern neural network architecture for inference on hardware accelerators

Preferred Qualifications

- PhD and 1 years of relevant experience

- Experience optimizing end-to-end real-world AI workloads

- Familiarity with OpenVINO or other AI inference frameworks

- Knowledge of neural network optimization techniques and performance tradeoffs

- Experience across multiple layers of the AI software stack, including:

• AI inference engines or runtimes
• Graph compilers (e.g., MLIR/LLVM)
• GPU kernels or performance critical compute code

- Performance profiling and workload analysis

Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Experienced Hire

Shift 1 (United States of America)

US, California, Folsom

US, California, Santa Clara, US, Oregon, Hillsboro

The Software Team drives customer value by enabling differentiated experiences through leadership AI technologies and foundational software stacks, products, and services. The group is responsible for developing the holistic strategy for client and data center software in collaboration with OSVs, ISVs, developers, partners and OEMs. The group delivers specialized NPU IP to enable the AI PC and GPU IP to support all of Intel's market segments. The group also has HW and SW engineering experts responsible for delivering IP, SOCs, runtimes, and platforms to support the CPU and GPU/accelerator roadmap, inclusive of integrated and discrete graphics.

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.N/A

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $170,500.00-240,710.00 USD

The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.

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.

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ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.

We are looking for an experienced AI Software Development Engineer to drive end-to-end optimization of AI inference workloads on Intel GP - Us. This is a vertical workload optimization role spanning graph compilation, runtime execution, and low-level GPU kernels, delivering measurable performance improvements for modern AI models. Key Responsibilities - Optimize emerging AI inference workloads such as Large Language Models (LL - Ms) and Diffusion models on GP - Us - Develop and optimize graph-based compilation flows (e.g., MLIR/ LLVM) for neural network workloads - Write and tune performance-critical GPU kernels and runtime code in C or parallel programming languages - Identify and resolve bottlenecks across compiler, runtime, and kernel layers - Profile, benchmark, and characterize AI workloads to validate performance gains - Collaborate with hardware, driver, and framework teams on hardware/software co-optimization. What We're Looking for Professional traits: - Excellent problem-solving abilities and strong attention to detail. Qualifications:Qualifications. Minimum Requirements - Bachelor's degree with 4 years of relevant experience, OR Master's degree with 2 years of relevant experience in Computer Science or a related field. The experience must include: - Strong C development and debugging skills - Solid understanding of GPU architectures or AI accelerators - Hands-on experience with modern neural network architecture for inference on hardware accelerators. Preferred Qualifications - PhD and 1 years of relevant experience - Experience optimizing end-to-end real-world AI workloads - Familiarity with Open. VINO or other AI inference frameworks - Knowledge of neural network optimization techniques and performance tradeoffs - Experience across multiple layers of the AI software stack, including:AI inference engines or runtimes. Graph compilers (e.g., MLIR/ LLVM)GPU kernels or performance critical compute code - Performance profiling and workload analysis. Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research. Job Type:Experienced Hire. Shift:Shift 1 (United States of America)Primary Location: US, California, Folsom.

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