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2026 Annapurna Labs at AWS, Early Career (US) - Machine Learning Systems & Silicon Innovation

ID: 6732

Type: Full-time

Category: Others

Company Name: Annapurna Labs (U.S.) Inc. - D63

Location: USA, TX, Austin; USA, WA, Seattle; USA, CA, Cupertino - Cupertino - United States

Salary: 127,100.00 - 185,000.00 USD annually

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Job Description

What if you could help build something that's never existed before? At Annapurna Labs, an Amazon company, we're not just participating in the AI revolution – we're accelerating it. We design custom silicon and revolutionary software systems that were considered impossible just yesterday, powering the world's most advanced AI infrastructure at AWS. From training the largest language models on Earth to developing breakthrough ML accelerator chips, we're inventing the future of cloud computing.

We're seeking bold innovators and builders for our 2026 Early Career roles. This isn't your typical early career role - at Annapurna Labs, you'll work on projects that directly impact millions of AWS customers worldwide, tackling real technical challenges that push the boundaries of what's possible in AI acceleration. Our program offers multiple technical tracks, matching your skills and interests with projects across our organization.

Want to architect next-generation AI chips that process billions of parameters? Build distributed systems that scale across thousands of accelerators? Create compiler optimizations that make ML training blazingly fast? Whether your passion lies in hardware design, distributed systems, compiler development, or ML infrastructure, we'll help you find your perfect fit and make meaningful contributions from day one.

Some of our technical tracks include:

🔹 ML Systems & Compilers
• Framework Optimization (PyTorch, JAX)
• Compiler Development & Optimization
• Distributed Training Systems
• Performance Engineering
• ML Infrastructure Development

🔹 Systems Software & Infrastructure
• Firmware & Driver Development
• Runtime Systems
• Fleet Management & Automation
• Hardware/Software Integration
• Performance Analysis Tools

🔹 Silicon Innovation & Design
• RTL Development for ML Accelerators
• Hardware Architecture & Modeling
• Physical Design & Power Optimization
• Custom Circuit Design
• Pre/Post Silicon Validation

Your placement will be determined through our interview process, taking into account your technical background, interests, and the exciting projects we have in development. One application opens the door to all these opportunities, so we'll work together to find where you can learn the most and have the biggest impact.

Basic Qualifications

- Experience programming languages such as C/C++, Python, Java or Perl
- BS, MS, or PhD in Computer Science, Computer Engineering, Applied Science, Electrical Engineering, Mechanical Engineering or related technical field
- Experience in two or more of the following areas: 1. Hardware design (RTL, System Verilog, FPGA development) 2. Systems programming or low-level software development 3. Compiler design or optimization 4. Machine learning frameworks (PyTorch, JAX, TensorFlow) 5. Distributed systems or parallel computing 6. Performance analysis and optimization

Preferred Qualifications

- Previous industry, internship, research, or project experience in hardware/software co-design, ML systems, or computer architecture
- Contributions to open-source projects or research publications
- Completed or currently enrolled in coursework covering machine learning, parallel computing, computer architecture and/or compiler construction

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 - 127,100.00 - 185,000.00 USD annually
USA, TX, AUSTIN - 110,500.00 - 160,000.00 USD annually
USA, TX, Austin - 110,500.00 - 160,000.00 USD annually
USA, WA, SEATTLE - 110,500.00 - 160,000.00 USD annually
USA, WA, Seattle - 110,500.00 - 160,000.00 USD annually

Company Information

Company Name: Annapurna Labs (U.S.) Inc. - D63

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

Company Address: USA, TX, Austin

Annapurna Labs is a technology engineering organization acquired by Amazon in January 2015 and integrated into Amazon Web Services (AWS). Originally founded as an independent semiconductor and systems-design startup, Annapurna Labs has since focused on the design and development of custom silicon, system-on-chip (SoC) solutions, and hardware subsystems used to optimize cloud infrastructure. The organization’s engineering work concentrates on creating purpose-built processors and hardware accelerators that improve performance, efficiency, security, and cost for hyperscale cloud services and virtualized computing environments. Annapurna Labs’ outputs are primarily incorporated into AWS compute, storage, and networking offerings rather than sold as products under the Annapurna brand to third-party customers. Company overview and positioning Annapurna Labs began as a specialized design team focused on low-power, high-performance SoCs and platform controllers suitable for consumer and data-center uses. After acquisition by Amazon, the group’s charter shifted to delivering hardware and firmware innovations that directly support AWS services and the EC2 compute platform. The team’s responsibilities include architecture, logic design, firmware, hardware engineering, and close integration with software and systems teams across AWS to enable differentiated instance types and infrastructure features. Engineers from Annapurna Labs collaborate with other AWS organizations to translate cloud service requirements (for performance, security, and scalability) into silicon and hardware subsystems integrated into Amazon’s data centers. Core business activities and capabilities Annapurna Labs’ core activities center on custom silicon design and hardware subsystem development for cloud infrastructure. Key capabilities include designing ARM-based processors and SoCs optimized for server workloads, developing dedicated virtualization and I/O offload hardware, and engineering secure, high-throughput networking and storage controllers. The organization also develops firmware, platform-level security features, and hardware-software co-design techniques to ensure that accelerators are tightly integrated with hypervisors, host operating systems, and AWS control plane services. Annapurna Labs’ engineering scope spans multiple layers of the stack: microarchitecture and CPU subsystem design; integration of memory, I/O, and accelerators on SoCs; board- and chassis-level hardware design; firmware and secure boot implementations; and the development of hardware subsystems that offload virtualization, networking, and storage tasks from general-purpose CPUs. This hardware-offload approach reduces overhead on server CPUs, enables higher consolidation and isolation for multi-tenant cloud environments, and allows AWS to offer instance types with improved price/performance profiles. Main products, technologies, and contributions While Annapurna Labs does not primarily market stand-alone commercial products under its own brand following the Amazon acquisition, its engineering output is visible across several AWS technologies and product families. Notable contributions linked to Annapurna Labs engineering include the AWS Nitro System and the Graviton family of processors. The AWS Nitro System is a collection of hardware and lightweight hypervisor software components that offload networking, storage, and security functions from host CPUs to dedicated hardware and firmware. Nitro enables improved performance, stronger isolation, and feature-rich instance types. The Graviton processors are AWS’s family of custom ARM-based CPUs designed for cloud workloads; these processors emphasize high throughput and energy efficiency for many server-use cases. Engineers from the Annapurna Labs organization have been reported as major contributors to the architecture and delivery of these initiatives. Beyond processors and Nitro, the group has focused on high-performance network controllers, storage controllers, and platform controllers that help AWS implement features such as enhanced networking, accelerated storage I/O, and hardware-enforced isolation. Annapurna Labs’ designs emphasize a hardware-software co-design approach: firmware and microcontroller subsystems are developed alongside host-level drivers and management software so that new hardware features can be exposed to AWS services and customers reliably and securely. This deep integration reduces virtualization overhead, improves I/O determinism, and enables new instance capabilities that would be difficult to achieve with off-the-shelf server components. Customers and deployment context Following the Amazon acquisition, Annapurna Labs’ technologies are principally deployed inside Amazon’s own global cloud footprint. The group’s work directly benefits AWS customers through improved EC2 instance performance, new instance families, and enhanced underlying infrastructure security and isolation. Rather than selling silicon or hardware directly to external customers, Annapurna Labs’ output is realized as AWS features, instance types, and managed services that incorporate their designs. This model allows Amazon to differentiate its cloud offerings by optimizing the underlying hardware for the specific demands of large-scale cloud workloads. Corporate and historical notes Annapurna Labs was founded as a private startup focused on SoC and hardware innovation. Amazon acquired the company in 2015, bringing its engineering talent into AWS. Since the acquisition, the team has been cited in AWS announcements and technical disclosures describing custom silicon and hardware systems used to advance AWS compute and virtualization technology. The organization operates as part of Amazon’s broader investment in custom infrastructure, in which in-house hardware design is used to achieve performance, cost, and feature advantages at hyperscale. In summary, Annapurna Labs is a specialized hardware engineering organization now operating within Amazon Web Services, responsible for designing custom processors, SoCs, and hardware subsystems that power and differentiate AWS compute and infrastructure services. Their work is built into internal AWS products (notably Nitro and the Graviton processor families) and focuses on improving performance, security, and efficiency for cloud customers through hardware-software co-design and purpose-built silicon.
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