GPU Software Development Engineer

AI in this role

Develop AI solutions and automated validation test content for GPU graphics drivers using modern machine learning frameworks and LLMs.

claudepytorchtensorflowscikit-learnkerascpythongpt

prompt-engineeringragfine-tuningsoftware-validationmachine-learninggenerative-aigpu-programmingllm

Job Details:

Job Description:

Are you passionate about software validation, developing tools and AI Solutions, automating software validation process at scale . Then GPU IP Graphics team has opportunities for you. Our Graphics validation team is creating AI solutions, complex test tools and automated tests for Kernel Mode driver, Memory Managers, Virtualization graphics and compute apps automation at scale. We deliver Intel's Software Graphics, media, display driver solutions across client, server and embedded markets. This position requires involvement in all phases of design from pre-silicon emulation/simulation through post-silicon product launch, covering aspects of functionality, power and performance and debuggability. You will also get opportunities to work on innovation projects utilizing modern GenAI technologies to implement advanced AI solutions to domain specific content. In this position, you will have the opportunity to work with multiple teams such as OS Microsoft, BIOS, HW, Customer Engineering, multiple Graphics SW teams etc. The candidate should have passion for technology and software, outstanding communication and teamwork skills. In this position you will be responsible for working across Hardware and Software Architecture, Design, Simulation, development and Validation throughout the product lifecycle to deliver high performing, scalable and power efficient hardware and software solutions.

Qualifications:

Minimum Qualifications • Bachelor's degree with 8+ years of experience or Master's degree with 7+ years of software development or validation experience. • Degree should be Computer Engineering or Computer Science • Hands on experience with one or more programming languages (C/C++) and/or scripting languages (Python) • Proficient in AI/ML frameworks (TensorFlow, PyTorch, Keras, scikit-learn) • Experience in defining validation strategy and test plans, developing automated tests, driving debug for issue resolution • A good understanding of Generative AI and LLMs: Possess knowledge of Generative AI and LLMs like Claude, GPT, Opus, with proven ability to train these models for information retrieval and Agentic/Skill Workflow applications to design and deploy GPU Driver Val test content • Strong experience with graphic drivers, GPU hardware and low level GPU programming • Ability to understand Intel Graphics HW and relevant specifications needed to develop/validate the software • Experience working in systems (hardware/software) product development teams • Strong attention to technical details, data analysis, documentation, problem solving and influencing skills, along with ability to work with different geographical locations • Strong written and verbal communication skills • Desire and ability to quickly learn and gain new knowledge Preferred Qualifications: • Experience in Kernel Mode driver development, power management, memory management, scheduler, virtualization, and other components of kernel mode driver including Operating System Concepts • Strong development experience in C/C++/Python • Familiarity with customization techniques at any level of the RAG pipeline such as model fine tuning, retrieval re-ranking, and hierarchical node parsing • Proven skills in using AI/ML techniques using structured and unstructured data • Knowledge of LLM fine tuning techniques like LoRA, PEFT, usage of pipelines, and other techniques like RAG, Prompt Engineering, Agentic and Skill based workflows automation

Job Type:

Experienced Hire

Shift:

Shift 1 (India)

Primary Location:

India, Bangalore

Additional Locations:

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

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.

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.

How we rate this

GPU Software Development Engineer at Intel rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

GPU Software Development Engineer is an open job at Intel.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in India, Bangalore.
The job was posted on October 7, 2026.
Seniority: senior.
Applications are handled by Intel. Apply on Intel

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt engineeringRAGFine-tuningSoftware ValidationMachine learningGenerative AIGPU ProgrammingLLM

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Tell me about a project where software validation was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Prompt engineering, RAG, Fine-tuning, Software Validation, and Machine learning. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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