Applied Scientist, AWS Neuron Science Team

ID: 6261

Type: Full-time

Category: Others

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

Location: USA, CA, Santa Clara - Santa Clara - Cuba

Salary: 171,600.00 - 222,200.00 USD annually

Job Description

The AWS Neuron Science Team is looking for talented scientists to enhance our software stack, accelerating customer adoption of Trainium and Inferentia accelerators. In this role, you will work directly with external and internal customers to identify key adoption barriers and optimization opportunities. You'll collaborate closely with our engineering teams to implement innovative solutions and engage with academic and research communities to advance state-of-the-art ML systems. As part of a strategic growth area for AWS, you'll work alongside distinguished engineers and scientists in an exciting and impactful environment. We actively work on these areas:

- AI for Systems: Developing and applying ML/RL approaches for kernel/code generation and optimization
- Machine Learning Compiler: Creating advanced compiler techniques for ML workloads
- System Robustness: Building tools for accuracy and reliability validation
- Efficient Kernel Development: Designing high-performance kernels optimized for our ML accelerator architectures

A day in the life
AWS Utility Computing (UC) provides 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, Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Additionally, this role may involve exposure to and experience with Amazon's growing suite of generative AI services and other cloud computing offerings across the AWS portfolio.

About the team
AWS Neuron is the software of Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best-in-class ML inference performance at the lowest cost in the cloud to our AWS customers. Trainium is designed to deliver the best-in-class ML training performance at the lowest training cost in the cloud, and it’s all being enabled by AWS Neuron. Neuron is a Software that include ML compiler and native integration into popular ML frameworks. Our products are being used at scale with external customers like Anthropic and Databricks as well as internal customers like Alexa, Amazon Bedrocks, Amazon Robotics, Amazon Ads, Amazon Rekognition and many more.

About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred 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.

Why 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
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

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.

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.

Basic Qualifications

- PhD in computer science, computer engineering, or related field
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience programming in Java, C++, Python or related language
- Experience using Unix/Linux

Preferred Qualifications

- Experience in investigating, designing, prototyping, and delivering new and innovative system solutions
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow

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, Santa Clara - 171,600.00 - 222,200.00 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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