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Sr. Software Development Engineer, Frontier AI & Robotics

职能机器学习
级别资深
地点Seattle, WA, United States
方式现场办公
类型全职
发布1个月前
立即申请

必备技能

Machine Learning

Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers like Pieter Abbeel, Rocky Duan, and Peter Chen to make breakthrough foundation models run at production scale. As a Senior Machine Learning Engineer embedded in our science team, you'll be instrumental in transforming innovative research into high-performance production systems. You'll collaborate directly with scientists to optimize large-scale transformer architectures for robotics applications, leveraging your expertise in CUDA and TensorRT to achieve unprecedented inference efficiency at Amazon scale.

In this role, you'll balance deep technical optimization work with strategic input on model architecture decisions, ensuring our innovative robotics models are designed with performance in mind from the ground up. You'll leverage NVIDIA's acceleration stack and other compilation techniques to tackle ambitious performance targets, working at the intersection of large language models and real-world robotics applications.

  • Key job responsibilities

  • Drive inference optimization strategies for large-scale foundation models using TensorRT, CUDA, and other NVIDIA tools

  • Collaborate closely with scientists to influence model architectures for optimal hardware utilization

  • Design and implement efficient compilation pipelines for complex transformer architectures

  • Develop comprehensive benchmarking frameworks to measure and optimize model performance

  • Build robust monitoring solutions to ensure reliable model serving at scale

  • Explore and evaluate emerging optimization techniques including ONNX Runtime and other ML compilers

  • Maintain high engineering standards through proper testing, documentation, and code review practices

  • A day in the life

  • Optimize transformer blocks using custom CUDA kernels and TensorRT optimization techniques

  • Partner with scientists to analyze model architectures and propose efficiency improvements

  • Implement and benchmark various optimization strategies for large-scale models

  • Debug performance bottlenecks using NVIDIA profiling tools

  • Participate in technical discussions about new model architectures with the science team

  • Design and maintain performance monitoring systems for production deployment

  • Prototype new acceleration approaches using emerging compilation frameworks

About the team
At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team, led by pioneering AI researchers Pieter Abbeel, Rocky Duan, and Peter Chen, is building the future of intelligent robotics through innovative foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios.
What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations.

Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

Basic Qualifications

  • Bachelor's degree in computer science or equivalent
  • 5+ years of non-internship professional software development experience
  • 5+ years of programming with at least one software programming language experience
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience as a mentor, tech lead or leading an engineering team
  • Strong expertise in Python, C++ and CUDA programming
  • Experience with TensorRT or similar ML optimization frameworks
  • Track record of optimizing ML models for production

Preferred Qualifications

  • Expertise in NVIDIA's ML stack (cuDNN, CUDA Graph, etc.)
  • Experience with ML compilers (ONNX Runtime, TVM, etc.)
  • Experience with transformer model optimization
  • Background in performance profiling and optimization
  • Experience working directly with research teams
  • Track record of building robust monitoring systems
  • Experience with large-scale ML serving systems

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.

Pursuant to the San Francisco 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, San Francisco - 193,300.00 - 261,500.00 USD annually
USA, WA, Seattle - 168,100.00 - 227,400.00 USD annually

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关于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+

员工数

Seattle

总部位置

$1.5T

企业估值

评价

10条评价

3.4

10条评价

工作生活平衡

2.5

薪酬

4.2

企业文化

3.0

职业发展

3.8

管理层

2.7

65%

推荐率

优点

Great benefits and competitive pay

Learning and advancement opportunities

Good teamwork and colleagues

缺点

High pressure and long hours

Poor work-life balance

Toxic work culture and management issues

薪资范围

4个数据点

Junior/L3

L2

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

L3

L4

L5

Junior/L3 · Data Scientist L4

0份报告

$181,968

年薪总额

基本工资

-

股票

-

奖金

-

$154,672

$209,264

面试评价

6条评价

难度

4.0

/ 5

时长

21-35周

体验

正面 0%

中性 17%

负面 83%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Technical Interview

6

Onsite/Virtual Interviews

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge