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- Back Distributed Training Validations and Automation EngineerJOB_DESCRIPTION.SHARE.HTMLCAROUSEL_PARAGRAPHJOB_DESCRIPTION.SHARE.HTMLSan Jose, California Engineering72886USD $226,400.00/Yr.USD $339,600.00/Yr.mail_outline Get future jobs matching this search Loginor Register Job Description WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. THE ROLE: AMD is looking for an AI solutions validation Engineer who is passionate about complex AI solutions, AI infrastructure, building cluster scale automation for distributed training and inference workloads, MLOps. 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. THE PERSON: The ideal candidate should be passionate about software engineering, system design, validation, automation and possess leadership skills to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD. KEY RESPONSIBILITIES: Work with AMD’s architecture specialists to validate AI solutions for distributed training and inference workloads with AMD's ROCM software Build cluster scale automation for distributed training and inference workloads Publish reference designs and benchmark numbers for AI workloads Apply a data minded approach to target optimization efforts Design and develop new groundbreaking AMD technologies Participating in new ASIC and hardware bring ups Develop technical relationships with peers and partners PREFERRED EXPERIENCE: Good experience with complex compute systems used in AI, HPC deployments, backend network designs in RDMA clusters Experience in validating complex AI infrastructure
- GPUs, networking, ROCEv2, UEC, running benchmark tests like IBPerf benchmarking, RCCL/NCCL. Experience with running training of LLMs, MoE models, Image Generation, recommendations models with different frameworks like Py Torch, Tensorflow, Megatron-LM, JAX. Running training performance benchmarks.
Experience with running inference workloads in AI clusters with different inference frameworks like vLLM, SGLang. Running performance benchmarks for inference.
Experience with distributed systems and schedulers like Kubernetes, Slurm Ability to write high quality automation frameworks and scripts using Python or Golang Experience with performance profiling of CPUs, GPUs and debugging complex compute, network, storage problems.
Experience with AMD ROCM would be an added advantage Experience with Linux, Windows operating systems Effective communication and problem-solving skills PREFERRED ACADEMIC CREDENTIALS: Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent
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About AMD

AMD
PublicA semiconductor company that designs and develops graphics units, processors, and media solutions
10,001+
Employees
Santa Clara
Headquarters
Reviews
3.5
25 reviews
Work Life Balance
3.2
Compensation
4.1
Culture
3.6
Career
3.4
Management
3.1
65%
Recommend to a Friend
Pros
Good compensation and benefits
Positive work environment
Great management and coworkers
Cons
Poor work life balance
Micromanagement and excessive tracking
Too much pressure and workload
Salary Ranges
6 data points
L2
L3
L4
L5
L6
M3
M4
M5
M6
L2 · Graphic Designer L2
0 reports
$162,512
total / year
Base
$65,005
Stock
$81,256
Bonus
$16,251
$113,758
$211,266
Interview Experience
5 interviews
Difficulty
3.6
/ 5
Duration
14-28 weeks
Offer Rate
60%
Experience
Positive 20%
Neutral 20%
Negative 60%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Technical Interview
5
Hiring Manager Interview
6
Offer
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
Past Experience
System Design
News & Buzz
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