Sr. Machine Learning - Compiler Engineer III, AWS Neuron, Annapurna Labs

ID: 5434

Type: Full-time

Category: Others

Company Name: Annapurna Labs (U.S.) Inc.

Location: USA, CA, Cupertino - Cupertino - United States

Salary: 193,300.00 - 261,500.00 USD annually

Job Description

Do you want to be part of AI revolution? At AWS our vision is to make deep learning pervasive for everyday developers and to democratize access to cutting-edge infrastructure. In order to deliver on that vision, we’ve created innovative software and hardware solutions that make it possible. AWS Neuron is the SDK that optimizes the performance of complex ML models executed on AWS Inferentia and Trainium, our custom chips designed to accelerate deep-learning workloads
This role is for a senior software engineer in the Compiler team for AWS Neuron. As part of this role, you will be responsible for building next generation Neuron compiler which transforms ML models written in ML frameworks (e.g, PyTorch, TensorFlow, and JAX) to be deployed AWS Inferentia and Trainium based servers in the Amazon cloud. You will be responsible for solving hard compiler optimization problems to achieve optimum performance for variety of ML model families including massive scale large language models like Llama, Deepseek, and beyond as well as stable diffusion, vision transformers and multi-model models. You will be required to understand how these models work inside-out to make informed decisions on how to best coax the compiler to generate optimal implementation instruction. You will leverage your technical communications skill to partner with other teams and will be involved in pre-silicon design, bringing new products/features to market, and many other exciting projects. Experience in object-oriented languages like C++/Java is a must, experience with compilers or building ML models using ML frameworks on accelerators (e.g., GPUs) is preferred but not required. Experience with technologies like OpenXLA, StableHLO, MLIR will be added bonus!
Explore the product and our history! https://awsdocs-neuron.readthedocs-hosted.com/en/latest/neuron-guide/neuron-cc/index.html
https://aws.amazon.com/machine-learning/neuron/
https://github.com/aws/aws-neuron-sdk
https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

Key job responsibilities
You will design, implement, test, deploy and maintain innovative software solutions to transform Neuron compiler’s performance, stability and user-interface. You will work side by side with chip architects, runtime/OS engineers, scientists and ML Apps teams to seamlessly deploy cutting edge ML models from our customers on AWS accelerators with optimal cost/performance benefits. You will have opportunity to become front-face of Neuron Compiler to work with open-source communities (e.g., StableHLO, OpenXLA, MLIR) and influence industry wide partners to pioneer optimizing cutting-edge ML workloads on AWS software and hardware. You will also work on building innovative features that will deliver best possible experiences for our customers – developers across the globe.

A day in the life
As you design and code solutions to help our team drive efficiencies in compiler architecture, you’ll create compiler optimization and verification passes, build features surface features and peculiarities of AWS accelerators to developers, implement tools to analyze numerical errors, and resolve the root cause of compiler defects. You’ll also participate in design discussions, code review, and communicate with internal (other Neuron SDK and Amazon wide teams) and external stakeholders (open-source communities and respond to Neuron compiler related questions in open forums, e.g. GitHub). Lastly, work in a startup-like development environment, where you’re always working on the most important stuff.

About the team
About the Team

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.

Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

About AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Basic Qualifications

- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 2+ years of experience in developing compiler features and optimizations
- Proficiency with 1 or more of the following programming languages: C++ (preferred), C, Python

Preferred Qualifications

- Master or PhD degree in computer science or equivalent
- Proficiency with resource management, scheduling, code generation, and compute graph optimization
- Experience optimizing Tensorflow, PyTorch or JAX deep learning models
- Experience with multiple toolchains and Instruction Set Architectures

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, CA, Cupertino - 193,300.00 - 261,500.00 USD annually

Company Information

Company Name: Annapurna Labs (U.S.) Inc.

Company Website: https://annapurna-labs.com

Company Address: 10201 Torre Avenue, Cupertino, California 95014, USA

Annapurna Labs (U.S.) Inc. is the U.S. corporate entity of Annapurna Labs, an engineering organization originally founded as a semiconductor and systems-on-chip (SoC) design company that was acquired by Amazon in 2015 and subsequently integrated into Amazon Web Services (AWS). The business is organized around the design and delivery of custom silicon, hardware acceleration engines, and tightly integrated hardware–software platforms used to improve performance, security, and efficiency of cloud infrastructure. Annapurna Labs operates as an engineering and product-development organization whose principal output is purpose-built silicon, firmware, and supporting software stacks that are deployed inside AWS data centers and products. Company overview: Annapurna Labs began as a privately held microelectronics and chip-design startup with an emphasis on low-power, high-density compute and specialized accelerators. After acquisition by Amazon, the group continued as an internal Amazon/AWS engineering organization, focused on developing devices and subsystems that address bottlenecks in cloud servers and networking equipment. The organization is widely credited in official Amazon/AWS materials and public communications with designing and delivering several generations of custom AWS silicon and the enabling hardware subsystems that underpin notable AWS services and instance families. Core business activities: Annapurna Labs’ core activities center on end-to-end silicon and platform engineering: architecture, RTL and logic design, physical implementation, verification, firmware, board design, and the software integration required to bring custom chips into production at hyperscale. Key technical specializations include SoC and CPU core design, network and storage offload engines, hardware virtualization and security enclaves, high-speed interconnects, and low-level system software to exploit hardware capabilities. Instead of operating as a customer-facing chip vendor, the organization’s outputs are integrated into AWS infrastructure and services—its primary “customers” are AWS teams and the cloud customers that rely on AWS services. Main products and services: Public and official AWS communications associate Annapurna Labs with multiple internal silicon and platform programs that have been announced or described by Amazon. Notable outcomes attributable to the group include the AWS Nitro System, a collection of dedicated hardware and firmware components that offload virtualization functions (such as network and storage I/O and security isolation) from host CPUs, enabling higher performance and stronger isolation for EC2 instances; and the Graviton family of Arm‑based processors (Graviton and subsequent Graviton2/Graviton3 generations), which provide high performance per watt and are used in a wide range of EC2 instance types. Annapurna Labs’ technology has also contributed to AWS’s custom accelerators and specialized chips for inference and other workloads, along with supporting board and subsystem designs used across AWS server fleets. Operational model and customers: Following its acquisition, Annapurna Labs functions primarily as an in-house R&D and product engineering organization for Amazon/AWS rather than as a standalone commercial vendor selling chips directly to third parties. Its deliverables are integrated into AWS compute, storage, and networking products to improve throughput, reduce cost and power consumption, and enable new service capabilities. Through these integrations, AWS customers—enterprises, startups, and public-sector users—indirectly benefit from Annapurna Labs’ designs in the form of new instance types, specialized acceleration options, and platform-level features (for example, enhanced virtualization security provided through Nitro). Technology and integration focus: Annapurna Labs emphasizes hardware–software co-design, meaning the group develops chips and the low-level firmware and drivers required to expose their capabilities to higher-level cloud services. This includes designing secure firmware stacks, silicon-based root-of-trust features, and hardware acceleration engines for packet processing, storage offload, and cryptographic operations. The designs are intended to scale in rack- and data-center-level deployments; consequently, the organization also contributes to manufacturing qualification, supply-chain integration, and operational tooling required to bring new silicon into production across AWS’s global infrastructure. Strategic impact and role inside AWS: The creation and deployment of custom silicon and Nitro-class offload engines have been described in AWS materials as foundational to certain performance, security, and cost-efficiency improvements across Amazon’s cloud offerings. Annapurna Labs’ designs have enabled AWS to introduce distinct product capabilities—such as high-density, energy-efficient Arm-based compute instances and dedicated hardware paths for I/O and isolation—that differentiate AWS services in performance-per-dollar metrics and security posture. While Annapurna Labs itself is not a public-facing product company, its engineering outputs are a strategic enabler for AWS’s infrastructure roadmap and service portfolio. Publicly disclosed collaborations and communications: Details about Annapurna Labs and its projects have been shared in Amazon press releases, AWS blog posts, technical presentations, and regulatory filings since the acquisition. Those official channels describe the group’s role in developing the Nitro System and custom processors, as well as the subsequent use of that technology in EC2 instance families and other AWS services. As an entity, Annapurna Labs (U.S.) Inc. is a legal corporate unit tied to Amazon’s organizational and intellectual-property structure, responsible for managing U.S.-based engineering operations, compliance, and aspects of the commercial integration of its technologies within AWS. Limitations on external sales: Unlike independent semiconductor companies that market chips to a broad set of third-party OEMs, Annapurna Labs’ outputs are primarily intended for integration into Amazon/AWS infrastructure. As a result, most technical and product announcements emphasize the benefits delivered via AWS services rather than standalone Annapurna-branded products sold directly to external customers.

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