Logo
AMD

Distributed Training Validations and Automation Engineer

AMD, San Jose, California, United States, 95199

Save Job

Distributed Training Validations and Automation Engineer Get AI‑powered advice on this job and more exclusive features.

This range is provided by AMD. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

What You Do at AMD 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.

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

Participate 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, recommendation models with different frameworks like PyTorch, 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

Benefits Benefits offered are described: AMD benefits at a glance.

Equal Opportunity AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee‑based recruitment services. AMD and its subsidiaries are equal‑opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third‑party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

#J-18808-Ljbffr