Senior Staff Performance Engineer

Please Note:

To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period. 

Advancing the World’s Technology Together

Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you’ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what’s possible and powering the future. 

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We’re dedicated to empowering people to be their true selves. Together, we’re building a better tomorrow for our employees, customers, partners, and communities.

Please Note:

To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6-month period. 

Advancing the World’s Technology Together

Our technology solutions power the tools you use every day--including smartphones, electric vehicles, hyperscale data centers, IoT devices, and so much more. Here, you’ll have an opportunity to be part of a global leader whose innovative designs are pushing the boundaries of what’s possible and powering the future. 

We believe innovation and growth are driven by an inclusive culture and a diverse workforce. We’re dedicated to empowering people to be their true selves. Together, we’re building a better tomorrow for our employees, customers, partners, and communities.

Location: Daily onsite presence at our San Jose, CA office / U.S. headquarters in alignment with our Flexible Work policy.

What You’ll Do

• Build and operate AI environments that reflect production workloads, including agentic workflows, distributed inference, disaggregated serving architectures, and MoE deployments.

•  Collect workload traces, runtime telemetry, and performance data across the software stack from AI applications.

•  Characterize and compare workloads across environments and platforms, identifying compute, memory, communication, and scheduling bottlenecks from applications and frameworks to runtimes, hosts, and devices.
• Communicate findings to hardware architects, systems engineers, and software researchers through reports, presentations, and architecture reviews.
• Define performance evaluation methodologies and benchmarking standards for adoption across hardware and software teams, and set the technical direction for workload characterization.

What You Bring

• BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent industry experience. Required industry experience: 10+ years with a BS, 8+ years with an MS, or 5+ years with a PhD in performance engineering, AI systems, distributed systems, high-performance computing, or a related area. Candidates with additional experience and a record of technical leadership across teams may be considered at the Senior Staff level.

• Ability to interpret workload traces, runtime telemetry, and performance data to identify bottlenecks and explain their underlying causes, including how workload characteristics interact with specific operations and mechanisms within software and hardware layers.

• Knowledge of the LLM software stack, including serving and scheduling, attention and KV-cache management, kernel launch and memory-transfer overhead, and collective communication, and how these interact with accelerator compute throughput, memory hierarchy, memory bandwidth, and interconnect topology.

• Experience characterizing agentic workflows, long-context processing, MoE models, or disaggregated inference deployments.

• Experience profiling and optimizing AI workloads on NVIDIA GPU platforms using Nsight Systems and Nsight Compute, with analysis informed by GPU execution, memory hierarchy, and communication mechanisms.

• Experience analyzing multi-node AI deployments, including synchronization overhead, load imbalance, communication patterns, and scaling behavior.

• Experience with AI frameworks or serving systems such as PyTorch, vLLM, SGLang, TensorRT-LLM, DeepSpeed, Ray, or Megatron-LM.

Equal Opportunity Employment Policy 

Samsung Semiconductor takes pride in being an equal opportunity workplace dedicated to fostering an environment where all individuals feel valued and empowered to excel, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status.

When selecting team members, we prioritize talent and qualities such as humility, kindness, and dedication. We extend comprehensive accommodations throughout our recruiting processes for candidates with disabilities, long-term conditions, neurodivergent individuals, or those requiring pregnancy-related support. All candidates scheduled for an interview will receive guidance on requesting accommodations.

Our Commitment to Innovation and Fairness

At Samsung Semiconductor, we use Artificial Intelligence (AI) tools in the recruitment process to enhance efficiency. However, AI is used as a support tool, not a final decision-maker. All hiring decisions are made by our human recruiting team and hiring managers to ensure every candidate is evaluated fairly and holistically.

Recruiting Agency Policy

We do not accept unsolicited resumes. Only authorized recruitment agencies that have a current and valid agreement with Samsung Semiconductor, Inc. are permitted to submit resumes for any job openings.

Applicant AI Use Policy 

At Samsung Semiconductor, we support innovation and technology. However, to ensure a fair and authentic assessment, we ask that candidates rely on their own knowledge and skills throughout the process. AI tools may be used for basic preparation, grammar, and research, but should not be used to generate or assist with submitted content or live interview responses. If we determine that AI is being used outside these guidelines, we reserve the right to pause or end the interview, and your candidacy may be disqualified.

Trade Secret Notice

By submitting an application, you agree not to disclose to Samsung—or encourage Samsung to use—any confidential or proprietary information (including trade secrets) belonging to a current or former employer or other entity.

Applicant Privacy Policy
https://semiconductor.samsung.com/about-us/careers/us/privacy/