Job description

  • Currently enrolled or recently completed a graduate degree program (either MS or PhD) in Electrical Engineering, Computer Science, Computer Engineering, Mathematics, or related field with specialization in machine learning, NLP, ASR, Deep Learning, Computer Vision, Automated Reasoning, Quantum Computing, or related fields.
  • Experience and knowledge of programming languages such as C/C++, Java, or Python (SciPy, RPy2, etc.)
Are you excited about developing state-of-the-art Scientific, Machine Learning, Natural Language Processing, Deep Learning and Computer Vision algorithms and designs using large data sets to solve real world problems? Do you have proven analytical capabilities and can multi-task and thrive in a fast-paced environment? Do you want to build a foundation for your career after your Master's or PhD program at an industry-leading company?

Our scientists enjoy solving real-world problems that, quite frankly, have not been solved at scale anywhere before. Along the way, you���ll get opportunities to be a fearless disruptor, prolific innovator, and a reputed problem solver—someone who truly enables computer science and machine learning to create significant impacts.

As an Machine Learning Engineer, you will bring statistical modeling and machine learning advancements to data analytics for customer-facing solutions in complex industrial settings. You will be working in a fast-paced, cross-disciplinary team of researchers who are leaders in the field. You will take on challenging problems, distill real requirements, and then deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even need to deliver these to production in customer facing products.

We offer flexible year round start dates for fulltime roles.

Notable research areas include:
  • Cloud and systems: https://www.amazon.science/research-areas/cloud-and-systems
  • Computer Vision: https://www.amazon.science/research-areas/computer-vision
  • Conversational AI / NLP: https://www.amazon.science/research-areas/conversational-ai-natural-language-processing
  • Information and knowledge management: https://www.amazon.science/research-areas/information-and-knowledge-management
  • Machine Learning: https://www.amazon.science/research-areas/machine-learning
  • Operations research and optimization: https://www.amazon.science/research-areas/operations-research-and-optimization
  • Quantum: https://www.amazon.science/research-areas/quantum-technologies
  • Search: https://www.amazon.science/research-areas/search-and-information-retrieval
  • Security: https://www.amazon.science/research-areas/security-privacy-and-abuse-prevention
Apply today to help us research and build the future!

https://aws.amazon.com/

About Us
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.

  • Research experience related to relevant research topic including but not limited to ML, DL, NLP, CV
  • Published and/or presented papers at top conferences associated with relevant research topics including but not limited to ICASSP, ICML, KDD, CVPR, EMNLP, NeurIPS, etc.
Amazon is committed to a diverse and inclusive workforce. Amazon is an equal opportunity employer and does not discriminate on the basis of race, ethnicity, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us

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