Job Details:

Job Description: 

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:

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.

          

Job Type:

Experienced Hire

Shift:

Shift 1 (United States of America)

Primary Location: 

US, California, Folsom

Additional Locations:

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

Business group:

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.

Posting Statement:

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.

Position of Trust

N/A

Benefits

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.