Cloud Hardware Dev Engineer Intern

Amazon is hiring a Cloud Hardware Dev Engineer Intern. Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this role Little AI ●○○○: aI is not part of the work.
Level classes it as an internship.
Amazon has 20,000+ other open roles on Level.
Posted within the past week.

AI in this role

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 software, hardware, and network 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.

Key job responsibilities
- Collaborate with vendors/manufacturers to evaluate new hardware and software features and come up with implementation plans for incorporating them into the network.
- Automate optical test plans and qualify optical modules.
- Focus on ambiguous problem areas in existing or new network architecture and systems development initiatives, propose and deliver projects that have a significant business and/or customer impact.
- Drive mindful discussions with customers and peers, be a key influencer in team strategy.
- Work with network operations team in identifying operation issues and improving quality and RMA process.
- Monitor module quality in the fleet and build mechanism to remediate large scale events and improve health of our links

A day in the life
On an everyday basis as an engineer or scientist in our team, you have the unique opportunity to understand the growing AWS network and our internal customers’ requirement on interconnect solutions, and work backwards to devise hardware solutions by influencing the broad industry and/or to develop software tools with sister teams to maintain a highly available network that delights AWS customers. You design and implement processes and mechanisms that both help the team to deliver business impact to the organization in a systemic way, while also helping to raise the bar on our operational excellence.

About the team
About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

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 in the cloud.

Basic qualifications

- Bachelor’s degree in Electrical/Electronic Engineering, Physics, Computer Engineering or equivalent worked experience.
- Interested in optical communication systems or components, optical transceivers, active electrical cables and IEEE standards.
- Professional script development experience with Python or a similar scripting language for automation.

Preferred qualifications

- Master or PhD degree in Electrical/Electronic Engineering, Physics, Computer Engineering or equivalent worked experience.
- In depth expertise in hardware or firmware, systems design and development. Expertise in debugging and troubleshooting.
- Experience with design pluggable optics, AEC, and NPO/CPO
- Deep knowledge of optical MSAs (OSFP, QSFP-DD) and the CMIS specification,
- Experience working in hyperscale cloud, AI or high-performance computing environments

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.

How we rate this

Cloud Hardware Dev Engineer Intern at Amazon rates 34 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.