Sr. Principal Machine Learning Software Engineer – Inference Serving Engine

Ampere Computing; Durham (NC); Híbrido; USD 225.000 - 339.000; Jornada completa

Descripción de la vacante

Ampere Computing LLC in Durham, North Carolina, seeks a Sr. Principal Machine Learning Software Engineer to lead the architecture and development of high‑performance AI inference‑serving software for Ampere accelerators.

You will work across model serving, frameworks, compilers, runtimes, and optimized kernels to enable efficient deployment of modern AI workloads, including generative AI and large language models, solving complex systems and performance challenges.

Formación

• Bachelor’s degree or higher in a technical field with extensive experience.
• Production inference runtimes and high-performance AI systems experience.
• Proficiency with C++ and systems-level performance optimization.
• Experience with profiling, benchmarking, and low-level debugging.
• Ability to lead cross-functional technical initiatives and communicate with stakeholders.

Responsabilidades

• Lead architecture and development of high-performance AI inference-serving software.
• Drive end-to-end serving performance, including throughput and latency.
• Develop capabilities such as batching, scheduling, model loading, and memory planning.
• Collaborate with model-serving, framework, compiler, runtime, kernel, and hardware teams.
• Mentor engineers and lead technical decisions across initiatives.
• Partner with product, field, and customer teams to prioritize capabilities.

Educación

Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Electrical Engineering, or a related technical field

Master’s degree with 8+ years

Ph.D. with 5+ years

Herramientas

vLLM

llama.cpp

TensorRT/TensorRT-LLM

ONNX Runtime

OpenVINO

Triton Inference Server

TVM

XLA

MLIR

CUDA

SYCL

OpenCL

MPI

Descripción del empleo

Sr. Principal Machine Learning Software Engineer – Inference Serving Engine

Ampere is a semiconductor design company for a new era, leading the future of computing with an innovative approach to CPU design focused on high-performance, energy efficient AI compute.

As a pioneer in the new frontier of energy efficient high-performance computing, Ampere is part of the Softbank Group of companies driving sustainable computing for AI, Cloud, and edge applications.

About the Role

As a Sr. Principal Machine Learning Software Engineer, you will lead the architecture and development of high-performance AI inference-serving software for Ampere accelerators. You will work across model serving, frameworks, compilers, runtimes, and optimized kernels to enable efficient deployment of modern AI workloads, including generative AI and large language models.

This is a hands‑on technical leadership role for someone who can solve complex systems and performance challenges while influencing the broader AI software and hardware roadmap.

What You’ll Achieve:

• Architect and build an inference-serving engine that supports and optimizes state-of-the-art AI models on Ampere deep learning accelerators.
• Drive end‑to‑end serving performance, including throughput, latency, tail latency, memory efficiency, scalability, and cost per inference.
• Develop key serving capabilities such as batching and scheduling, KV-cache management, model loading, memory planning, quantization, and multi‑device or distributed inference.
• Collaborate across model‑serving, framework, compiler, runtime, kernel, and hardware teams to deliver a cohesive, high-performance AI software stack.
• Optimize model execution through graph compilation, operator fusion, precision optimization, efficient attention, and hardware‑specific execution strategies.
• Influence future accelerator architecture through hardware/software co‑design, translating real‑world AI workload requirements into product recommendations.
• Establish technical direction, design standards, benchmarking practices, and performance‑validation processes for the serving platform.
• Evaluate, integrate, and contribute to relevant open‑source AI serving and runtime technologies.
• Mentor engineers and lead technical decisions across cross‑functional initiatives.
• Partner with product, field, and customer teams to prioritize capabilities and deliver production‑ready AI solutions.

About You:

• Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Electrical Engineering, or a related technical field with 12+ years of relevant experience; master’s degree with 8+ years; or Ph.D. with 5+ years.
• Experience developing or optimizing production inference runtimes, serving engines, deployment toolkits, or high‑performance AI systems.
• Experience with technologies such as vLLM, llama.cpp, TensorRT/TensorRT-LLM, ONNX Runtime, OpenVINO, Triton Inference Server, TVM, XLA, MLIR, or comparable systems.
• Expert proficiency in modern C++ and strong experience in C, including concurrent programming, memory management, and systems‑level performance optimization.
• Strong understanding of AI inference performance, including batching, scheduling, latency/throughput tradeoffs, memory bandwidth, KV-cache behavior, quantization, and accelerator utilization.
• Experience with profiling, benchmarking, performance analysis, and low‑level systems debugging.
• Demonstrated ability to lead complex cross‑functional technical initiatives and communicate effectively with software, hardware, and product stakeholders.

Preferred Qualifications

• Experience with LLM, transformer, multimodal, or generative‑AI inference.
• Experience with AI frameworks and heterogeneous computing technologies such as PyTorch, oneDNN, SYCL, OpenCL, OpenMP, MPI, CUDA, ROCm, or similar platforms.
• Experience with ML compilers, graph optimization, code generation, kernel development, or device runtimes.
• Familiarity with distributed inference, cloud‑native serving, containers, Kubernetes, orchestration, observability, or multi‑tenant systems.
• Experience with model optimization techniques, including mixed precision, INT8/INT4/FP8 quantization, sparsity, or efficient-attention methods.
• Experience collaborating with hardware architecture teams on hardware/software co‑design.
• Contributions to relevant open‑source AI, compiler, runtime, or HPC projects.

What We’ll Offer:

At Ampere we believe in taking care of our employees and providing a competitive total rewards package that includes base pay, cash long‑term incentive, and comprehensive benefits. The full base pay range for this role is between $225,500 and $338,500, except in the San Francisco Bay Area where the range is between $237,000 and $356,000.

Our benefits include health, wellness, and financial programs that support employees through every stage of life.

Benefit highlights include:

• Premium medical insurance, dental insurance, vision insurance, as well as income protection and a 401K retirement plan, so that you can feel secure in your health and financial future.
• Unlimited Flextime and 10+ paid holidays so that you can embrace a healthy work‑life balance.
• A variety of healthy snacks, energizing espresso, and refreshing drinks to keep you fueled and focused throughout the day.

And there is much more than compensation and benefits. At Ampere, we foster an inclusive culture that empowers our employees to do more and grow more. We are excited to share more about our career opportunities with you through the interview process. Our benefits include health, wellness, and financial programs that support employees through every stage of life.

#LI-Hybrid

#LI-Hybrid #LI-DR #LI-Hybrid

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Description

Invent the future with us. Ampere is a semiconductor design company for a new era, leading the future of computing with an innovative approach to CPU design focused on high‑performance, energy efficient AI compute. As a pioneer in the new frontier of energy efficient high‑performance computing, Ampere is part of the Softbank Group of companies driving sustainable computing for AI, Cloud, and edge applications.

About the Role

As a Sr. Principal Machine Learning Software Engineer, you will lead the architecture and development of high‑performance AI inference‑serving software for Ampere accelerators. You will work across model serving, frameworks, compilers, runtimes, and optimized kernels to enable efficient deployment of modern AI workloads, including generative AI and large language models.

This is a hands‑on technical leadership role for someone who can solve complex systems and performance challenges while influencing the broader AI software and hardware roadmap.

What You’ll Achieve:

• Architect and build an inference‑serving engine that supports and optimizes state‑of‑the‑art AI models on Ampere deep learning accelerators.
• Drive end‑to‑end serving performance, including throughput, latency, tail latency, memory efficiency, scalability, and cost per inference.
• Develop key serving capabilities such as batching and scheduling, KV-cache management, model loading, memory planning, quantization, and multi‑device or distributed inference.
• Collaborate across model‑serving, framework, compiler, runtime, kernel, and hardware teams to deliver a cohesive, high‑performance AI software stack.
• Optimize model execution through graph compilation, operator fusion, precision optimization, efficient attention, and hardware‑specific execution strategies.
• Influence future accelerator architecture through hardware/software co‑design, translating real‑world AI workload requirements into product recommendations.
• Establish technical direction, design standards, benchmarking practices, and performance‑validation processes for the serving platform.
• Evaluate, integrate, and contribute to relevant open‑source AI serving and runtime technologies.
• Mentor engineers and lead technical decisions across cross‑functional initiatives.
• Partner with product, field, and customer teams to prioritize capabilities and deliver production‑ready AI solutions.

About You:

• Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Electrical Engineering, or a related technical field with 12+ years of relevant experience; master’s degree with 8+ years; or Ph.D. with 5+ years.
• Experience developing or optimizing production inference runtimes, serving engines, deployment toolkits, or high‑performance AI systems.
• Experience with technologies such as vLLM, llama.cpp, TensorRT/TensorRT-LLM, ONNX Runtime, OpenVINO, Triton Inference Server, TVM, XLA, MLIR, or comparable systems.
• Expert proficiency in modern C++ and strong experience in C, including concurrent programming, memory management, and systems‑level performance optimization.
• Strong understanding of AI inference performance, including batching, scheduling, latency/throughput tradeoffs, memory bandwidth, KV-cache behavior, quantization, and accelerator utilization.
• Experience with profiling, benchmarking, performance analysis, and low‑level systems debugging.
• Demonstrated ability to lead complex cross‑functional technical initiatives and communicate effectively with software, hardware, and product stakeholders.

Preferred Qualifications

• Experience with LLM, transformer, multimodal, or generative‑AI inference.
• Experience with AI frameworks and heterogeneous computing technologies such as PyTorch, oneDNN, SYCL, OpenCL, OpenMP, MPI, CUDA, ROCm, or similar platforms.
• Experience with ML compilers, graph optimization, code generation, kernel development, or device runtimes.
• Familiarity with distributed inference, cloud‑native serving, containers, Kubernetes, orchestration, observability, or multi‑tenant systems.
• Experience with model optimization techniques, including mixed precision, INT8/INT4/FP8 quantization, sparsity, or efficient‑attention methods.
• Experience collaborating with hardware architecture teams on hardware/software co‑design.
• Contributions to relevant open‑source AI, compiler, runtime, or HPC projects.

What We’ll Offer:

At Ampere we believe in taking care of our employees and providing a competitive total rewards package that includes base pay, cash long‑term incentive, and comprehensive benefits. The full base pay range for this role is between $225,500 and $338,500, except in the San Francisco Bay Area where the range is between $237,000 and $356,000.

Our benefits include health, wellness, and financial programs that support employees through every stage of life.

Benefit highlights include:

• Premium medical insurance, dental insurance, vision insurance, as well as income protection and a 401K retirement plan, so that you can feel secure in your health and financial future.
• Unlimited Flextime and 10+ paid holidays so that you can embrace a healthy work‑life balance.
• A variety of healthy snacks, energizing espresso, and refreshing drinks to keep you fueled and focused throughout the day.

And there is much more than compensation and benefits. At Ampere, we foster an inclusive culture that empowers our employees to do more and grow more. We are excited to share more about our career opportunities with you through the interview process. Our benefits include health, wellness, and financial programs that support employees through every stage of life.

#LI-Hybrid

#LI-DR #LI-Hybrid

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Ampere is an inclusive and equal opportunity employer and welcomes applicants from all backgrounds. All qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, religion, age, veteran and/or military status, sex, sexual orientation, gender, gender identity, gender expression, physical or mental disability, or any other basis protected by federal, state or local law.