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职位Amazon

Sr. Manager of Colocation, Machine Learning, Data Center Supply Solutions

Amazon

Sr. Manager of Colocation, Machine Learning, Data Center Supply Solutions

Amazon

Austin, TX, USA

·

On-site

·

Full-time

·

1w ago

The Sr. Manager of Colocation Machine Learning leads a team of individual contributors across AMER responsible for developing and scaling AWS' Machine Learning infrastructure through strategic colocation partnerships. This role manages the initial stage of lifecycle of ML-focused colocation deals, from vendor identification and commercial negotiations to contract execution. The Sr. Manager ensures operational excellence, contractual compliance, and infrastructure reliability for ML workloads while serving as an escalation point for internal stakeholders and external partners. Key responsibilities include developing internal and external partnerships, overseeing commercial transactions (New sites, Expansions, MTSAs, and amendments), and mitigating infrastructure risks specific to ML deployments. This leader collaborates cross-functionally with Operations, Engineering, Finance, and Legal to optimize colocation strategies that support AWS' ML service scaling initiatives. The role requires deep expertise in ML infrastructure requirements, vendor management, commercial negotiations, and the ability to influence senior leadership while empowering team members to deliver continuous improvements in support of AWS customer experience.

Key job responsibilities
-Manage the commercial and operational relationships with assigned infrastructure partners
. Own cadence and content of our team's internal business review schedule, including reporting
. Manage and evolve our IPM partner performance dashboards
. Support the need for reporting from our business support systems

A day in the life
-Manage commercial relationships with infrastructure partners
-Hire, cultivate, coach, and train individual contributors on the business development team
-Drive cost savings and avoidance initiatives
-Stay current on the latest engineering and technical requirements in the industry
-Serve as escalation point for internal stakeholders and external partners on ML-specific infrastructure matters
-Collaborate cross-functionally with Operations, Engineering, Security, and Product teams to optimize colocation strategies supporting AWS' ML service scaling
-Present strategy to high level leadership

About the team
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.

You’ll join a diverse team of Business developers, engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

Basic Qualifications

  • 3+ years of management experience
  • Experience hiring candidates, mentoring and developing employees in their careers
  • 6+ years of multi-million dollar contract negotiation experience
  • 6+ years of Colocation Experience

Preferred Qualifications

  • 5+ years of management experience
  • Experience in large complex deal negotiations with a successful track record

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

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, TX, Austin - 173,800.00 - 235,000.00 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

2.9

10条评价

工作生活平衡

2.8

薪酬

3.7

企业文化

2.5

职业发展

2.3

管理层

2.1

35%

推荐给朋友

优点

Good pay and compensation

Strong benefits package

Flexible scheduling options

缺点

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

薪资范围

4个数据点

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份报告

$181,968

年薪总额

基本工资

-

股票

-

奖金

-

$154,672

$209,264

面试经验

10次面试

难度

3.7

/ 5

时长

21-35周

录用率

20%

体验

正面 10%

中性 10%

负面 80%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge