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  • The site is refreshed daily to remove out-of-date content.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.
Home View All Jobs (2,302,471)

Job Information

Amazon Senior Applied Scientist, AWS Shanghai AI Lab in Shanghai, China

Description

DESCRIPTION

The AWS Shanghai AI Lab is looking for a passionate, talented, and inventive staff in all AI domains with a strong machine learning background as a Senior Applied Scientist.

Founded in 2018, the Shanghai Lab has been an innovation center of for long-term research projects across domains as machine learning, computer vision, natural language processing, and open-source AI system. Meanwhile, these incubated projects power products across various AWS services.

As part of the lablet, you will take a leadership role and join a vibrant team with a diverse set of expertise in both machine learning and applicational domains. You will work on state-of-the-art solutions on fundamental research problems with other world-class scientists and engineers in AWS around the globe and across the boarders. You will have the responsibility to design and innovate solutions to our customers. You will build models to tame large amount of data, achieve industry-level scalability and efficiency, and along the way rapidly grow and build the team.

BASIC QUALIFICATIONS

  • 5+ years of experience after PhD in Electrical Engineering, Computer Science, or related disciplines. Strong expertise in machine learning.

  • World-class track record in one of the sub-application domains of machine learning (e.g. NLP, CV, speech, graph machine learning, etc); publication record in top ML conferences/journals such as NeurIPS, ICML, ICLR, etc.

  • Experience in building full-stack machine learning solutions from scratch, including training, debugging and performance optimization.

  • Proficient in Python. Experiences with AI/ML frameworks and open-source projects (e.g., PyTorch, TensorFlow) are preferred.

  • Good English written and spoken communication skills.

PREFERRED QUALIFICATIONS

  • Familiar with recent advances in domains as computer vision, natural language processing, multi-modality.

  • Critical and scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.

  • Sharp research taste. Experiences serving reviewers for top conferences/journals, AC/PC experiences are even better.

  • Experience in engineering practice of scalable, efficient, and highly optimized AI/ML production projects.

We are open to hiring candidates to work out of one of the following locations:

Shanghai, CHN

Basic Qualifications

  • 3+ years of building machine learning models for business application experience

  • PhD, or Master's degree and 6+ years of applied research experience

  • Experience programming in Java, C++, Python or related language

  • Experience with neural deep learning methods and machine learning

Preferred Qualifications

  • Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

  • Experience with large scale distributed systems such as Hadoop, Spark etc.

DirectEmployers