Senior Staff Performance Engineer
samsungsemiconductor
1 month ago
Full-time
On-site
San Jose, California, United States
$189,000 - $301,000 USD yearly
Engineering
Moneyboard classification: Published range reaches threshold
Reported USD annual base: $189,000–$301,000
Original source: Greenhouse
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.Â
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.Â
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.Â
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.Â
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.
The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. Our team is committed to designing and developing scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance. To achieve this goal, we collaborate closely with both hardware and software engineers to identify and address the unique challenges posed by AI/ML workloads and to explore new computing abstractions that can provide a better balance between the hardware and software components of our systems. Additionally, we continuously conduct research and development in emerging technologies and trends across memory, computing, interconnect, and AI/ML, ensuring that our platforms are always equipped to handle the most demanding workloads of the future. By working together as a dedicated and passionate team, we aim to revolutionize the way AI/ML applications are deployed and executed, ultimately contributing to the advancement of AGI in an affordable and sustainable manner. Join us in our passion to shape the future of computing!
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.
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What We Offer
The pay range below is for all roles at this level across all US locations and functions. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. We also offer incentive opportunities that reward employees based on individual and company performance.Â
This is in addition to our diverse package of benefits centered around the wellbeing of our employees and their loved ones. In addition to the usual Medical/Dental/Vision/401k, our inclusive rewards plan
Reported USD annual base: $189,000–$301,000
Original source: Greenhouse
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.Â
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.Â
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.Â
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.Â
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.
The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. Our team is committed to designing and developing scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance. To achieve this goal, we collaborate closely with both hardware and software engineers to identify and address the unique challenges posed by AI/ML workloads and to explore new computing abstractions that can provide a better balance between the hardware and software components of our systems. Additionally, we continuously conduct research and development in emerging technologies and trends across memory, computing, interconnect, and AI/ML, ensuring that our platforms are always equipped to handle the most demanding workloads of the future. By working together as a dedicated and passionate team, we aim to revolutionize the way AI/ML applications are deployed and executed, ultimately contributing to the advancement of AGI in an affordable and sustainable manner. Join us in our passion to shape the future of computing!
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.
Â
What We Offer
The pay range below is for all roles at this level across all US locations and functions. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. We also offer incentive opportunities that reward employees based on individual and company performance.Â
This is in addition to our diverse package of benefits centered around the wellbeing of our employees and their loved ones. In addition to the usual Medical/Dental/Vision/401k, our inclusive rewards plan