Machine Learning Engineer, AWS Developer Tools

Job summary
The AWS Developer Tools is looking for Machine Learning Engineers who are excited to join a new team responsible for building an innovative product that is set to redefine developer experience. We have an exciting charter that includes solving complex machine learning problems that will impact millions of developers every day.

In this role you will invent, implement, and deploy infrastructure and systems for state of the art machine learning algorithms, build prototypes, and explore conceptually new representation learning solutions at massive scale. You will interact closely with our customers and work on a team of engineers, scientists, and academics with diverse backgrounds. This role will provide exposure to cutting-edge ML innovations in information retrieval, deep learning and statistics, while working closely with researchers in building algorithms ranging from classical machine learning to state-of-the-art deep neural network models on diverse types of signals. You will have the opportunity to publish in scientific conferences and journals, create white papers, write blogs, and have high visibility in the industry. The ideal candidate will have experience with information retrieval systems and proficient in building, deploying and tuning machine learning models. We are particularly interested in experience applying natural language processing and deep learning at scale.

If you are a self-starter, enjoy formulating new ideas and rapidly prototyping, and are excited by challenging problems with few guardrails, this is a unique and rare opportunity to join a high powered team building from scratch. We operate like a start up, all while leveraging the full scale of assets and technologies of Amazon.

Location options include Seattle (WA), Bay Area (CA), Boston (MA), Arlington (VA) and New York City. Other location options may be considered.


Key job responsibilities
* Own scaling up successful prototypes and implementing a reliable automated production workflow for machine learning models.
* Partner with scientists and engineers on the team to investigate, evaluate, implement, and deploy sophisticated ML model to our ML platforms.
* Be hands-on and raise the bar on best practices for data collection, modeling, software development and experimentation
* Stay current on knowledge to keep pace with rapidly changing science and technology

Basic Qualifications

• Programming experience with at least one software programming language.
• 1+ years of experience in software development

Preferred Qualifications

* Bachelor's Degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
* Experience with common machine learning techniques such as preprocessing data, training and evaluation of classification and regression models, and statistical evaluation of experimental data.
* Experience building workflows involving large dataset and/or machine learning models in production using distributed computing and big data processing concepts and technologies.
* Experience related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2
* Experience building complex software systems that have been successfully delivered to customers
* Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
* Ability to take a project from scoping requirements through actual launch of the project


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.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.