Machine Learning Engineer II, Intl. Seller Growth, Central Analytics

Found in: Jooble US O C2 - 2 weeks ago

Seattle WA, United States Amazon Full time

Machine Learning Engineer II, Intl. Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
- 3+ years of data engineering experience
- Experience with machine learning techniques such as pre-processing data, training, hyper-parameter tuning and evaluation of classification and regression models, and statistical evaluation of experimental data.
Come and be part of the International Seller Services (ISS) Central Analytics Data Engineering (DE) team and work on solving cutting edge GenAI solutions
We are a team of DEs who support Applied Scientists, Data Scientist, and Economists who experiment, research, and turn machine/deep learning and AI research into great products for our customers.
ISS is seeking a smart, highly-motivated, and experienced Data Engineer to join our team. In this role, you'll help us create the right Data and ML infrastructure.
As a ML Data Engineer, you will provide technical expertise, lead ML engineering initiatives and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective. You carry projects from proof-of-concept to deployment and serving with a high standard for model maintenance and operations. You are passionate about working with huge unstructured and structured datasets and have experience with the organization and curation of data for analytics and model training. You have a strategic and long term view on architecting advanced data eco systems.
You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications.
You will bring in techniques for automating model training, evaluation, deployment and monitoring using machine learning pipelines. You will work 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.
Design, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science.
- Develop and deploy models and pipelines that scale
- Implement data ingestion routines using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.
- Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
- Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation
- Identify opportunities in existing data solutions for improvements
Example projects:
- Developing reusable cloud infrastructure and deployment patterns to accelerate productionalization
- Seattle, WA, USA - Knowledge of distributed systems as it pertains to data storage and computing
- Industry experience with one of more of the following domains: computer vision, deep learning, machine learning or large-scale distributed systems.
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
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.

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