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ASIC AI/ML Engineer, Annapurna Labs, MLA SOC, Methodology & Infrastructure

Amazon

ASIC AI/ML Engineer, Annapurna Labs, MLA SOC, Methodology & Infrastructure

Amazon

Tel Aviv, ISR

·

On-site

·

Full-time

·

2w ago

Our Machine Learning Acceleration (MLA) team develops the SOCs that are used to power today’s AI workloads in datacenters all around the world. As a Frontend ASIC engineer, you’ll contribute to the project at the ground level by automating workflows and developing large-scale solutions that accelerate silicon development - it’s still Day One here at Amazon!

We are seeking an experienced ASIC AI/ML Engineer with deep expertise in AI/ML infrastructure and application development specifically for semiconductor design verification disciplines. The ideal candidate will have a proven track record of delivering end-to-end AI solutions from concept to large-scale production deployment.

In this role, you will collaborate directly with architects, designers, verification engineers, software teams, and backend specialists to define best practices and deploy production-ready AI-driven workflows and applications. Your focus will be on implementing LLM, GenAI, and classical ML solutions that transform our ASIC design verification processes and accelerate our path to tape-out.

  • Key job responsibilities
  • Develop and maintain scalable AI/ML infrastructure for ASIC design and verification teams
  • Architect, develop, and deploy production-ready AI/ML applications for semiconductor design workflows
  • Design and implement GenAI solutions including LLMs and agentic AI systems for verification processes • Invent innovative AI-driven solutions to eliminate identified inefficiencies in design and verification flows
  • Establish best practices and standards for AI/ML application development in semiconductor environments
  • Create monitoring and observability frameworks for AI model performance in production design environments
  • Collaborate cross-functionally with architects, designers, verification engineers, and software teams
  • Research and evaluate emerging AI technologies for applicability to semiconductor design challenges

Basic Qualifications

  • Experience with modern ASIC/FPGA design and verification tools
  • Developed scalable AI/ML infrastructure for semiconductor design and verification teams
  • Creating and maintaining automation frameworks for design or verification
  • Practical semiconductor design/verification work experience

Preferred Qualifications

  • Current on emerging AI technologies for semiconductor design and verification applications
  • Proficient in full-stack development and infrastructure for state-of-the-art classic ML and generative AI technologies

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.

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About Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

Employees

Seattle

Headquarters

Reviews

2.9

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a Friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

2 data points

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L4

0 reports

$181,968

total / year

Base

-

Stock

-

Bonus

-

$154,672

$209,264

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge