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Description

If you’re curious, empathetic, and passionate about video technologies—and excited about applying innovative machine learning techniques—we want you as a team member! This is a position where you’ll get to be innovative and creative while working on challenging and impactful problems in the video space. You will prototype and integrate advanced models at scale, powering experiences used by customers all over the world, from small start-ups to major broadcasting companies.

As a Senior Applied Scientist on the team, you’ll be both a leader and a key technical contributor. A successful candidate has strong expertise in applied science (machine learning, artificial intelligence, data analysis) as well as effective communication and leadership skills, with experience mentoring and collaborating across disciplines. You must have a proven track record of delivering on your team’s most critical and challenging projects and the ability to listen empathetically to differing opinions, building consensus to guide the team toward a deeper understanding of a problem. You’ll need to be able to take ambiguous and complex problems and develop innovative models and algorithms that balance customer needs and timelines with long-term maintainability and scalability.

If you’re excited about media services and you want to grow your machine learning and applied science skills in a supportive environment, join our team and help customers get inspiring and compelling video content to their viewers!

Key job responsibilities

• Building prototypes, optimizing and deploying advanced machine learning models into production to solve complex challenges in video processing, understanding, and content monetization

• Collaborating with product management, engineers, and data scientists to design and drive the delivery of new customer-focused features and enhancements

• Developing scalable solutions to enhance quality, improve the performance, and resiliency of our video services through data-driven modeling and experimentation

• Participating in code and model reviews to help the team identify sharp edges, estimate edge cases, anticipate challenges, follow Amazon’s best practices for AIML, and improve the quality of scientific and engineering work

• Mentoring team members on machine learning best practices, advanced modeling techniques, and service improvements, fostering continuous growth in technical and research skills

• Contributing to operational tooling and improvements, including building metrics, dashboards, and monitoring solutions to ensure our systems and models perform reliably at scale

• Contributing towards publication of applied research work in conferences internally or externally

About the team

At Elemental, we focus on career growth and work with you to find projects that will help you succeed individually in your career while making the team successful. We will do our part to ensure you are challenged, while providing you with the tools, resources, and mentorship to support your development as a scientist.

We recognize that you spend a large number of your hours at work and we value the importance of feeling fulfilled and satisfied in your role. We will collaborate with you to create a work environment that makes you most productive and contented, recognizing that it looks different for everyone. We also respect your life outside of work, and we are flexible in how you manage your schedule so you can find a flow that fits your life.

AWS Infrastructure Services (AIS)

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Basic Qualifications

- 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

- Extensive experience developing and deploying large-scale machine learning systems, particularly in video processing or computer vision

- Expertise in large language models or demonstrated ability to develop this expertise quickly

- Deep expertise in modern deep learning frameworks and production ML systems

- Excellent written and verbal technical communication with an ability to present complex technical information in a clear and concise manner to a variety of audience

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.