Machine Learning Engineer, Amazon Tablets

Description du poste:

At Amazon Devices & Services, we believe that ideas can change the world. We build the technology that becomes part of everyday life and connects millions of people in ways never thought possible. We engineer high-profile consumer electronics, including the best-selling Kindle family of products. We have also produced game-changing devices like Fire tablets, Fire TV, Amazon Dash, and Amazon Echo. Join us as a Software Development Engineer to help us imagine the future, and let's make it reality together.

The Amazon Tablets Core Machine Learning team seeks to hire an ML Engineer who has a background in the design and development of scalable AI/ML systems, experience deploying models into production to serve millions of customers, a deep passion for building AI-driven products, and a proven track record of executing complex projects and delivering high business impact.

You will be an early member of the team -- together with your team members, you will play a key role in establishing a strong foundation for customer-focused machine learning on the team. This role will provide you with the opportunity to drive impact at Amazon-scale, as well as work closely with with ML scientists in a cross-functional organization.

The long-term vision of the team is to make Amazon devices effortlessly engaging for all our customers. We are creating an experience that understands why and when customers engage with different types of contents or take different actions, and build our products to foresee and satisfy those needs. We are building the capabilities to give Amazon devices the ability to help customers discover and find all types of relevant information and contents through conversational interactions, suggestions, and personalized recommendations. We are exploring ways to enable an intelligent customer experience by leveraging advanced deep learning and large language models, generative AI, and machine learning on device.

Key job responsibilities
As an ML Engineer, you will:
- Design and develop AI/ML products that involve large-scale data processing and modeling
- Be responsible to help define requirements, create software designs, implement code to these specifications, and support products while deployed and used by our customers
- Work with applied scientists, data scientists, engineers, and product managers to design and deliver AI/ML solutions in production at scale.
- Develop ML workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our ML systems and data infrastructure.
- Maintain and continuously improve our existing ML workflows, MLOps, and infrastructure.
- Deliver customer-facing and internal ML solutions that empower our devices to provide the best experience for our customers.

A day in the life
As a Machine Learning Engineer on our team, you will collaborate with product managers, UX designers, and fellow engineers to build end-user-facing features on the Home screen app. You will design, plan, and deliver mid-sized software features - learning, employing, and sometimes building the tools and techniques needed to create performant, resource-efficient, and stable mobile apps and AWS services. You will build and train models that deliver better recommendations and rank content based on user behavior.

About the team
We build the Home screen app - the face of Fire Tablets that millions of Amazon customers worldwide use everyday. Our goal is to continue making the Home screen app CX highly engaging, and personalized for the user; and enable new revenue opportunities for Amazon. And we take pride in building a functionally rich, content-forward and visually appealing app that exceeds the performance bar customers would expect on a low-budget tablet device. We are a team of engineers who can dive deep into Android, and at the same time build large scale services leveraging AWS

Profil requis du candidat:

- Experience (non-internship) in professional software development
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing
- Experience designing or architecting (design patterns, reliability and scaling) of new and existing systems
- Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
- Bachelor's degree in computer science or equivalent
- Experience in several of the following areas: machine learning, statistics, deep learning, natural language processing, or information retrieval
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations, or experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Experience in building scalable machine-learning infrastructure and big data systems.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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