Career Opportunities

Success Starts Here

As a leading global supplier of wafer fabrication equipment and services to the semiconductor industry, Lam Research develops innovative solutions that help our customers build smaller, faster, and more power-efficient devices.

This success is the result of our employees' diverse technical and business expertise, which fuels close collaboration and ongoing innovation.

Join the Lam Research team, where you can write your own success story. Come help us solve our customers' toughest problems and be part of a company that plays a vital role in the future of electronics.

Lam Research - a company where successful people want to work.

Engineering Infrastructure Architect

Date: Sep 13, 2018

Location: Fremont, CA, US, 94538

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Together we move the Atoms that move the World

“… We're on the cusp of one of the most exciting periods in the technology industry, and the semiconductor roadmap, the silicon device, and the industry of capital equipment. Lam Research, specifically, is right at the center of making that possible.” -Martin Anstice, CEO Lam Research


Imagine working on the front lines of innovation! As one of the semiconductor industry’s leading suppliers of wafer fabrication equipment and services, our technology depends on finding and hiring the best and the brightest employees. We know that our dynamic, global team of exceptional employees is essential to our continued growth.

 

Lam Research - where successful people want to work:

We are company comprised of people who work hard, deliver outstanding results and maintain a sense of humor during even the most challenging times. This is truly a rare opportunity. Lam Research is a market leader where our core values are not just words on the back of your badge. Given the criticality of this role to Lam Research’s success, this philosophy starts with you.

 

Engineering Infrastructure Architect

 

Responsibilities

  • Responsible for delivering and implementing solutions for Lam’s engineering environments. Focused on building large distributed systems deployments for our large scale IOT and high performance computing environments
  • Hands on experience in HPC – CPU/GPU based compute as well as distributed computing and Big Data (Hadoop based) platforms
  • Hands on experience in scoping latest hardware (cloud/on premise) and integrating HPC systems
  • Creating data pipelines and overall workflow orchestration to cover data needs for HPC platform
  • Iterate quickly through latest packages and R&D on latest information.
  • Work with Product Management and multiple business units for requirement gathering and iteratively refine architectural proposals
  • Support upstream and downstream use cases with integration with existing Big data ecosystem.

 

Desired Skills and Experience

  • Undergraduate/Ms degree/PhD in Computer Science or distributed systems
  • Experience with Linux based OS’s such as CentOS, Redhat, Ubuntu
  • 5 years’ experience in Java/C++/Object Oriented systems programming and/or python, shell scripting (e.g. bash, PowerShell)
  • Experience with distributed computing/storage technologies like Hadoop (Map/Reduce, HDFS, HBase, in memory compute etc.), containerization such as docker
  • Experience building and deploying enterprise scale applications, familiarity with GPU computing
  • Deep understanding of Machine learning, simulation, and massive parallel compute architectures
  • Performance analysis and optimization, experience architecting and deploying highly reliable systems (HA, ACID, guaranteed delivery etc.)
  • Experience with scalable computer architectures (on premise and cloud (private cloud e.g. Openstack))
  • Understand requirements and goals for distributed computing. Prior exposure to MOAB/SLURM and Cyclecloud strong plusses. Experience with InfiniBand and clustered file systems
  • Design the appropriate computing and storage architecture to meet the customer goals
  • Hands-on engagement in the build out and delivery of the architecture
  • Experience operating in a Hybrid cloud environment and connectivity, prior exposure to Azure IaaS or equivalent required

 

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