Student Veterans of America Jobs

Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

Here are a few things you should know:
  • This site is mobile friendly. You do not need a log-in or password to access information.
  • Jobs on this site are original and unduplicated and come from three sources: the Federal government, state workforce agency job banks, and corporate career websites. All jobs are vetted to ensure there are no scams, training schemes, or phishing.
  • The site is refreshed daily to remove out-of-date content.
  • The newest jobs are listed first, so use the search features to match your interests. You can look for jobs in a specific geographical location, by title or keyword, or you can use the military crosswalk. You may want to do something different from your military career, but you undoubtedly have skills from that occupation that match to a civilian job.
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Google Technical Specialist, AI Infrastructure and Machine Learning Operations in Taipei, Taiwan

Google welcomes people with disabilities.

Minimum qualifications:

  • Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.

  • 5 years of experience with cloud infrastructure.

  • Experience building and operationalizing machine learning models.

Preferred qualifications:

  • Experience training and fine-tuning large models (i.e., image, language, segmentation, recommendation, genomics) with accelerators.

  • Experience with performance profiling tools (i.e., Tensorflow profiler, PyTorch profiler, Tensorboard).

  • Experience designing/architecting large-scale infrastructure farms for specialist AI use cases.

  • Experience with running MLPerf benchmarks, distributed training and optimizing performance versus costs.

  • Familiarity with libraries and frameworks such as HuggingFace Transformers, CUDA, Pytorch, Pytorch/XLA etc.

  • Ability to engage with C-level or executive business leaders and influence decisions.

The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

In this role, you will guide customers with platform architecture, migration strategy, and analyze cost/performance benchmarks to help them train and serve ML models at scale. You will work closely with cross-functional AI teams, Product and Engineering, Infrastructure, and Kubernetes specialists to remove roadblocks and shape the future solutions for customers.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

  • Be a trusted advisor to customers, helping them understand and incorporate AI accelerators into their overall cloud strategy by recommending migration paths, integration strategies, and application architecture that incorporate Google Cloud AI optimized infrastructure.

  • Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on proof-of-concepts, demonstrating features, optimizing model performance, profiling, and bench-marking.

  • Build repeatable assets to enable other customers and internal teams.

  • Influence Google Cloud strategy at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements.

  • Travel to customer sites and events as needed.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCPEEOPost.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.

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