AI Models GPU Deployment Software Engineer

Overview

AMD is looking for a software engineer who is passionate about expanding AI models on AMD GPUs, and improving the performance of key applications and benchmarks. You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology.  

📌 Job Overview

Position: AI Models GPU Deployment Software Engineer

Industry: Information Technology

Employment Type: Full-Time

Locations: Hyderabad, India

Experience Required: 3-8+ Years

Salary Range: As per company standards and candidate experience

Note: Exact salary and benefits may vary depending on the company and role offered.

🎓 Educational Qualification

Masters or PhD or equivalent experience in Computer Science, Computer Engineering, or related field

💻 Required Technical Skills

Strong technical and analytical skills in C++/Python AI development in a Linux environment.

🧠 Soft Skills Required

Ability to work as part of a team, while also being able to work independently, define goals and scope and lead your own development effort. 

💼 Key Responsibilities

• Enable and optimize key AI models (LLM, Vision, MultiModal, etc.) on AMD GPUs 

• Optimize AI frameworks like PyTorch, TensorFlow, etc. on AMD GPUs in upstream open-source repositories 
• Collaborate and interact with internal GPU library teams to analyze and optimize training and inference for AI
• Work with open-source framework maintainers to understand their requirements – and have your code changes integrated upstream 
• Optimize GPU kernels, understand and drive AI operator performance (GEMM, Attention, etc.) with specialized teams
• Work in a distributed computing setting to optimize for both scale-up (multi-GPU) and scale-out (multi-node) systems 
• Apply your knowledge of software engineering best practices 

Preferred Qualifications:

• Knowledge of GPU computing (HIP, CUDA, OpenCL)
• AI model experience or knowledge – Natural Language Processing, Vision, Audio, Recommendation systems
• Excellent C/C++/Python programming and software design skills, including debugging, performance analysis, and test design. 
• Experiences to run workloads on large scale heterogeneous cluster is a plus 
• Experiences to optimize GPU kernels for performance is a plus

📝 Selection Process

While the exact recruitment process differs by company, most IT companies follow a structured hiring pattern:

Online Application Submission

Resume Shortlisting

Online Technical Assessment

Technical Interview

HR Interview

Some companies may include additional coding rounds or practical assignments.

Candidates are advised to prepare thoroughly for technical interviews and coding assessments.

📍 Locations & Work Model

AMD Offers :  Hybrid work model

📅 Important Application Details

Application Mode: Online

Application Status: Ongoing (subject to official notification)

Last Date: As mentioned on the official website

Applicants should regularly check the official website of the respective company for updated deadlines.

🔗How to Apply

• 1. Click on the “Click to Apply here” button provided below.
• 2. Click on “Apply”.
• 3. If you have not registered before, create an account.
• 4. After registration, log in and fill in the application form with all the necessary details.
• 5. Submit all relevant documents, if requested (e.g. resume, mark sheet, ID proof).
• 6. Verify that all the details entered are correct.
• 7. Submit the application form after verification.

❓ Frequently Asked Questions (FAQ)

1. What is an AI Models GPU Deployment Software Engineer?

2. Why are GPUs necessary for AI model deployment?

3. What are the key responsibilities in this role?

4. What tools and frameworks are essential?

5. How does the engineer improve inference performance?

⚠ Important Disclaimer

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All applicants are strongly advised to verify eligibility, deadlines, and official announcements directly from the respective company’s official website before applying.

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