Machine Learning Engineer

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- Bachelor's degree in computer science or equivalent
- 2+ years of relevant experience in developing and deploying large scale machine learning or deep learning models and/or systems into production, including batch and real-time data processing
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Masters or PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field
- Practical experience in solving complex problems in an applied environment
- Experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2
- Experiences related to machine learning, deep learning, NLP, CV, GNN, or distributed training
- Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts
- Comfortable working in a fast paced, highly collaborative, dynamic work environment

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI, ML and DL algorithms to solve real world problems with significant impact?

Amazon is revolutionizing customer service yet again now with cutting edge AI and ML. Device, Digital and Alexa Support (D2AS) is responsible for the Customer Service operations and solutions for all Amazon Devices and Digital products, from Kindle and Echo, to Amazon Music and Prime Video.

We’re seeking a Machine Learning Engineer to develop cutting-edge AI solutions leveraging Large Language Models (LLM), Machine Learning (ML) and Natural Language Processing (NLP) techniques to understand and resolve customer issues and provide earth's best customer service. We are looking for individuals with a passion for learning, researching, and deploying production-ready science solutions in a highly collaborative environment. We like to ideate, experiment, iterate, optimize and scale quickly, while thoughtfully balancing speed and quality.

Key job responsibilities
In this role, you will:
- Use ML and Generative AI tools, such as Amazon SageMaker and Amazon Bedrock, to provide a scalable production solutions to improve the customer experience, to label data, build, train, tune and deploy their models.
- Collaborate with our Applied and data scientists to create and fine tune scalable ML and Generative AI solutions for business problems.
- Interact with product stakeholders directly to understand the business problem, help and aid them in implementation of their ML ecosystem
- Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes.
- Work closely with science and engineering teams to drive model implementations and new algorithms.


A day in the life
We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment.

If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

Benefits summary:
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

About the team
We at D2AS strive to make digital experiences effortless for customers. Our goal is to anticipate, evaluate, prevent, and eliminate any effort required from customers. We achieve this by setting the strategy for digital support and accelerating the delivery of seamless support experiences across Amazon's digital products.
Our team combines strategic thinking, technology expertise, and customer experience best practices. This ensures customers can easily get the most value from Amazon's digital offerings. We focus on providing the right support at the right time, tailored to each customer's needs. By eliminating friction and making support effortless, we enhance the overall customer experience.