Sr. ML Kernel Performance Engineer, AWS Neuron, Annapurna Labs

Amazon; Asti; In loco; EUR 60.000 - 90.000; Tempo pieno

Descrizione del lavoro

A leading cloud service provider is seeking a Sr. ML Kernel Performance Engineer to optimize machine learning workloads on custom ML accelerators. Responsibilities include designing high-performance kernels, analyzing performance, and collaborating with customers. Candidates should have over 5 years of software development experience, expertise in programming languages, and a background in machine learning frameworks. This position fosters a unique learning culture and flexible work arrangements.

Servizi

Mentorship and career growth

Flexible working hours

Inclusive team culture

Competenze

• 5+ years of professional software development experience.
• Experience leading design and architecture of systems.
• Proficiency in ML frameworks like PyTorch and TensorFlow.

Mansioni

• Design and implement high-performance compute kernels for ML operations.
• Analyze and optimize kernel-level performance across Neuron hardware.
• Work directly with customers to optimize ML models on AWS accelerators.

Conoscenze

Low-level optimization

System architecture

ML model acceleration

Parallel programming

Formazione

Bachelor's degree in computer science or equivalent

Strumenti

CUDA

OpenCL

Descrizione del lavoro

Sr. ML Kernel Performance Engineer, AWS Neuron, Annapurna Labs

The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon’s custom machine learning accelerators, Inferentia and Trainium.

The Acceleration Kernel Library team is at the forefront of maximizing performance for AWS's custom ML accelerators. Working at the hardware-software boundary, our engineers craft high-performance kernels for ML functions, ensuring every FLOP counts in delivering optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration.

The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch, enabling unparalleled ML inference and training performance.

As part of the broader Neuron Compiler organization, our team works across multiple technology layers - from frameworks and compilers to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology.

This is an opportunity to work on cutting-edge products at the intersection of machine-learning, high-performance computing, and distributed architectures. You will architect and implement business-critical features, publish cutting-edge research, and mentor a brilliant team of experienced engineers. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We're inventing. We're experimenting. It is a very unique learning culture. The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their machine learning workloads achieve optimal performance on AWS ML accelerators.

Explore the product and our history. (We have included internal references to our documentation and resources.)

• Key job responsibilities: Our kernel engineers collaborate across compiler, runtime, framework, and hardware teams to optimize machine learning workloads for our global customer base. Working at the intersection of software, hardware, and machine learning systems, you'll bring expertise in low-level optimization, system architecture, and ML model acceleration.
• Design and implement high-performance compute kernels for ML operations, leveraging the Neuron architecture and programming models
• Analyze and optimize kernel-level performance across multiple generations of Neuron hardware
• Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks
• Implement compiler optimizations such as fusion, sharding, tiling, and scheduling
• Work directly with customers to enable and optimize their ML models on AWS accelerators
• Collaborate across teams to develop innovative kernel optimization techniques

A day in the life

As you design and code solutions to help our team drive efficiencies in software architecture, you’ll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You’ll also:

• Build high-impact solutions to deliver to our large customer base.
• Participate in design discussions, code review, and communicate with internal and external stakeholders.
• Work cross-functionally to help drive business decisions with your technical input.
• Work in a startup-like development environment, where you’re always working on the most important stuff.

About the team

• Diversity of experiences is valued. If you do not meet all qualifications, we encourage you to apply. If your career is just starting or follows a nontraditional path, don’t let it stop you from applying.
• Why AWS: Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and continuously innovate to power customer success.
• Inclusive team culture: We embrace differences and have multiple employee-led affinity groups and ongoing learning experiences. Our culture is aligned with our Leadership Principles.
• Work/Life balance: We value a healthy balance and offer flexibility in working hours.
• Mentorship & Career Growth: We support new members with a focus on knowledge sharing and professional development.

BASIC QUALIFICATIONS

• 5+ years of non-internship professional software development experience
• 5+ years of programming with at least one software programming language
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems
• Experience as a mentor, tech lead or leading an engineering team

PREFERRED QUALIFICATIONS

• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Bachelor's degree in computer science or equivalent
• Expertise in accelerator architectures for ML or HPC such as GPUs, CPUs, FPGAs, or custom architectures
• Experience with GPU kernel optimization and GPGPU computing such as CUDA, ROCm, OpenCL, SYCL, or similar
• Demonstrated experience with GPU ISA and/or LLVM/MLIR backend development for GPUs
• Experience developing high performance libraries for HPC applications
• Proficiency in low-level performance optimization for GPUs
• Knowledge of ML frameworks (PyTorch, TensorFlow) and their GPU backends
• Experience with parallel programming and optimization techniques
• Understanding of GPU memory hierarchies and optimization strategies

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit the Amazon accommodations page for more information.