The mission of the Machine Learning University (MLU) is to foster a community of ML practitioners who learn, apply, and advance ML knowledge. To do this, we develop educational programs and mechanisms that enable the tech community and engage scientists in teaching and mentoring others through our portfolio of programs.

With the recent advances in generative AI, we are looking to hire an instructor with deep knowledge of generative AI technology, and with proven experience applying it to solve concrete problems. We recognize that this is a new and evolving field and we look forward to seeing what you have done!

A successful candidate will be a passionate teacher with demonstrated ability to explain technical content (in particular machine learning, or generative AI content) to an audience of technical professionals, enhance curriculum, and coordinate with other instructors. Significant practical experience across domains and techniques are required to ensure content is up-to-date, practical and engaging. This is a full-time role where you will constantly be challenged to learn and be curious about all the unknown advances still to come. Help us demystify and democratize technology!

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

• Teach courses: Teach at least one 120 minute lecture per week and host matching multi-hour office hours to work with students on projects and assignments integrating practical generative AI skills in each lesson plan.
• Develop and revise curriculum: Coordinate with Amazon scientists and staff to enhance the practical relevance of class content and incorporate current use cases and applications.
• Collaborate with scientists: Support the continuous engagement with Amazon scientists who contribute to the program as instructors and technical consultants.
• Work with MLU program managers to ensure that students receive a high-quality, experience at the right level of technical depth ranging from conceptual familiarity to masters-level competency.

About the team
We pride ourselves on the fact that almost nobody on our team followed the direct path in life. We have come from many different backgrounds, and held many different careers before we all were brought together here to work together at MLU. This has repeatedly been a strength that has allowed us to tackle problems otherwise insurmountable.

The Amazon Consumables organization operates categories, programs, and technology designed to offer customers a frictionless shopping experience of Everyday Essential (EE) products. We do this through a variety of innovative programs including Subscribe and Save, Climate Pledge Friendly, Beauty Shopping Experience, Pets and Regionalized Selection that directly benefit hundreds of millions of Amazon customers across the world and drive tens of billions of dollars in revenue.
We’re seeking a Senior Principal Scientist to drive innovation across Consumables through applications of Machine Learning. Your responsibilities will include everything from developing and prototyping innovative machine learning, and deep learning algorithms to implementing, testing, and supporting full solutions in a production environment. You will serve as a strategic advisor to science, product, and engineering partners. You will be an intellectual thought leader that will help enhance the science in addition to developing the thinking of our team. You will direct and shape the science philosophy, planning and strategy for the organization on a variety of ML driven innovations. You will lead efforts in Generative AI to advance our customer feature set, and provide thought leadership to scientists and engineers to invent and implement scalable ML recommendations supporting new Customer Experiences. You will work closely with peers in Amazon Consumer to advance state of the art research and science application for our Machine Learning models. You’ll also participate in organizational planning, hiring, mentorship and leadership development.

Interested in Machine Learning (ML) and Artificial Intelligence (AI)? Do you want to join the team that is building AI/ML features that will disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast-paced environment?

Our team is leading the AI features of Amazon Connect. We are a team of scientists and AI/ML engineers working on multiple AI/ML projects, using state-of-the-art science and engineering practices to solve hard problems for our customers in the space of contact center operations, management and optimization.

Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. Amazon Connect is a publicly available service based on ten years of development building the tools Amazon itself uses to provide its award-winning customer service. With Amazon Connect, businesses can create their own cloud-based contact centers and begin taking calls in minutes. With this technology, we are transforming an industry and the way customers interact with businesses and how agents service them.

We are looking for a Senior Applied Scientist (Machine Learning) with a strong academic background and industry experience in the areas of stochastic modeling, queueing theory, anomaly detection and optimization.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers.

Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

The Creative X team sits within the Amazon Advertising team and aims to democratize access to high-quality creatives (images, videos) by building generative AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), computer vision (CV), reinforcement learning (RL), and image + video synthesis. The solutions we develop will be deployed for use by self-service advertisers and agencies, as well as available to the most premium brands that advertise on Amazon.

We are seeking an experienced science leader who is adept at a variety of skills; especially in generative AI, computer vision, latent diffusion, and large language models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. The right candidate will provide science leadership, establish the right direction and vision, build team mechanisms, and foster the spirit of collaboration and innovation within the org. The leader will provide both technical direction as well as manage a sizable team of scientists. The role will have a high degree of executive interaction.

Key job responsibilities
This role is focused on leading a science team focused on computer vision, latent diffusion models, and the related foundational models to product generative imagery and videos.
Responsibilities include:
* Drive end-to-end applied science projects that have a high degree of ambiguity, scale, complexity.
* Provide technical / science leadership related to computer vision, large language models, and generative image + video.
* Research new and innovative machine learning approaches.
* Recruit high performing Applied Scientists to the team and provide mentorship.
* Establish team mechanisms, including team building, planning, and document reviews.

Passionate about books? The Amazon Books personalization team is looking for a talented Applied Scientist III to help invent, design, and deliver cutting-edge science solutions to make it easier for millions of customers to find the next book they will love. In this role you will:

• Be a part of a growing and vibrant team of scientists, economists, engineers, analysts, and business partners.
• Use Amazon's large-scale computing and data resources to generate deep understandings of our customers, and products.
• Build models to generate recommendations and run them as large scale A/B tests directly on the retail website.
• Design, implement, and deliver novel solutions to some of Amazon's oldest problems.

Key job responsibilities
The role is focused on recommender systems bridging Natural Language Processing (NLP), Reinforcement Learning (RL), graph networks, and deep learning to help find the next great read for Books customers. You will build recommendation model pipelines, identify technical opportunities within complex deep learning-based recommendation models, and work with engineering and product leaders to power customer-facing recommendations.

As part of the team, you will be exposed to all of these areas and have opportunities to hone and apply your skills across our problem space.

A day in the life
From day-to-day, you will research and develop models that power customer facing recommendations, design and implement A/B test experiments, as well as collaborate with engineers, product, and other scientists to get machine learning solutions into production.

About the team
We are Books Personalization a collaborative group of 5-7 scientists, 2 product leaders, and 2 engineering teams that aims to help find the right next read for customers through high quality personalized book recommendation experiences. Books Personalization is a part of the Books Content Demand organization, which focuses on surfacing the best books for customers wherever they are in their current book journey.