Applied Scientist, AWS AI/ML

Key Skills

Java Programming, Leadership, Python Programming, C++, C Programming, SQL, AWS, Machine learning techniques, Deep Learning, Natural Language Processing (NLP), Algorithms, Amazon Elastic Compute Cloud-EC2, AWS Sagemaker, Mathematics

Job Description

Interested in machine learning and AI? Can you envision a future where technology is driven primarily by smarter machines?

As an Applied Scientist in AWS AI/ML, you will be driving many scientific breakthroughs to automate and help our customers build ML applications. The ideal candidate will be passionate about ML/AI technology transfer with an interest in meta-learning, continual learning and automated decision making. You will be working closely with software engineers so experience with cloud systems is a must. Our customers are deeply technical and the solutions we build for them are strongly coupled to technical feasibility.

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.

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.

Key job responsibilities

The right candidate will have the following responsibilities:

• Understand customer needs and translate those into ML/AI-based solutions
• Develop novel ML solutions that are robust, practical, and scalable which lay the foundation for improvement of existing or the creation of new products
• Contribute to open source software and publish results in academic journals and at conferences
• Partner with engineering teams to transfer viable solutions into products

A day in the life

We at AWS value individual expression, respect different opinions, and work together to create a culture where each of us is able to contribute fully. Our unique backgrounds and perspectives strengthen our ability to achieve Amazon's mission of being Earth's most customer-centric company.

About the team

The mission of AWS AI/ML is to make machine learning easy, fast, and universal across all of our customers. Our world class platform provides the services that runs 85% of all on-cloud machine learning through performance optimizations, machine learning tools, and SDKs to democratize machine learning. Our customers include scientists, data analysts, and ML engineers all building and deploying models through either SageMaker or self-managed instances on EC2/EKS.

If you are passionate about advances in deep neural networks, meta- and continual learning, and have a proven track record of bringing innovative research to customers, we would like to talk with you.

BASIC QUALIFICATIONS

• PhD in Electrical Engineering, Computer Science, Mathematics or Physics with specialization in natural language processing, machine translation, signal processing, or machine learning.
• Breadth and depth knowledge of ML learning algorithms.
• Familiarity with programming languages such as Python, Java, C/C++ or Perl.

PREFERRED QUALIFICATIONS

• 2+ years of relevant experience in industry and/or academia.
• Proven track record of successfully applying ML-based solutions to complex problems in business, science, or engineering.
• Experience in building natural language processing, natural language understanding and dialogue systems (e.g., commercial products or government projects)
• Solid Machine Learning background and hands-on experience with neural deep learning methods.
• Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.
• Solid software development experience.
• Good written and spoken communication skills.