Sr. Principal Machine Learning Software Engineer – Inference Serving Engine

Ampere; Santa Clara (CA); Presencial; USD 237.000 - 356.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

401K retirement plan

Paid holidays

Descripción de la vacante

Ampere is seeking a Sr. Principal Machine Learning Software Engineer to lead 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

Formación

• Proven experience building or optimizing production inference runtimes or serving engines.
• Deep understanding of batching, scheduling, latency/throughput tradeoffs.
• Strong systems-level programming and memory management skills.
• Experience with profiling, benchmarking and low-level debugging.

Responsabilidades

• Architect and lead an inference-serving engine on Ampere accelerators.
• Drive end-to-end serving performance, throughput and latency targets.
• Collaborate with model-serving, framework, compiler, and hardware teams.
• Implement batching, KV-cache, memory planning, and quantization.
• Shape hardware/software co-design directions for future accelerators.
• Mentor engineers and drive cross-functional technical initiatives.
• Evaluate open-source AI serving tools and integrate where appropriate.
• Partner with product and customer teams to prioritize capabilities.

Conocimientos

C++ expert

Performance optimization

AI inference

Systems knowledge

Profiling/debugging

Cross-functional leadership

Memory management

Concurrency

KV-cache knowledge

Educación

Bachelor’s in CS/CE/Math/EE

Master’s degree (advantage)

PhD (advantage)

Herramientas

CUDA

PyTorch

ONNX Runtime

TensorRT

MLIR

TVM

XLA

OpenVINO

Kubernetes

Descripción del empleo

Description

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, and 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.

At Ampere, we foster an inclusive culture that empowers our employees to do more and grow more. And there is much more than compensation and benefits. 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.

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.