Machine Learning Engineer, Amazon Tablets
Role details
Job location
Tech stack
Job description
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.
Requirements
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.