Software Development Engineer, Amazon SageMaker, AWS AmazonAI Machine Learning Platform
New York, New York, USA
Amazon.com
Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa...
Job summary
Interested in building ML-distributed systems to deploy machine learning models for inferencing at scale? With Amazon SageMaker, Amazon Web Service's (AWS) Machine Learning platform team is building customer-facing services to catalyze data scientists and software engineers in their machine learning endeavors. We have set out to build highly scalable and fault tolerant distributed clustering infrastructure for HPC. Specifically, the real-time inference component enables customers deploy ML models at scale to run high performant, low-latency CPU / Deep Learning workloads and monitor the quality of the models and data in production. ML Ops, CICD and A/B testing are in the mix as well for deploying models safely.
You will design, implement, test, document, and support cross-cutting services to help customers do machine learning at scale. You'll assist in gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture. You will serve as a key technical resource in the full development cycle, from conception to delivery and maintenance. You will produce comprehensive, usable software documentation; recommend changes in development, maintenance and system standards. You will own delivery of entire piece of the system and serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers. You will do everything from determining priorities and designing features to re-architecture as necessary, automated testing and mentoring others. The best candidates show true end-to-end ownership.
At SageMaker, there are immense learning as well as growth opportunities. This is a great team to come to have a huge impact on AWS and the world's customers we serve!
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
· 2+ years of non-internship professional software development experience
· Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
· 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
· Bachelor’s Degree in Computer Science, Computer Engineering or related field
· Solid Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis
· 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
· Experience defining system architectures and exploring technical tradeoffs
· Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
· Hands-on expertise in building and operating complex distributed systems
· Master's degree in Computer Science, Computer or Electrical Engineering or related field
· Experience building and operating mission critical, highly available (24x7) systems
· Experience with machine learning, data mining, and/or deep learning frameworks is a plus
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.
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.
Interested in building ML-distributed systems to deploy machine learning models for inferencing at scale? With Amazon SageMaker, Amazon Web Service's (AWS) Machine Learning platform team is building customer-facing services to catalyze data scientists and software engineers in their machine learning endeavors. We have set out to build highly scalable and fault tolerant distributed clustering infrastructure for HPC. Specifically, the real-time inference component enables customers deploy ML models at scale to run high performant, low-latency CPU / Deep Learning workloads and monitor the quality of the models and data in production. ML Ops, CICD and A/B testing are in the mix as well for deploying models safely.
You will design, implement, test, document, and support cross-cutting services to help customers do machine learning at scale. You'll assist in gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture. You will serve as a key technical resource in the full development cycle, from conception to delivery and maintenance. You will produce comprehensive, usable software documentation; recommend changes in development, maintenance and system standards. You will own delivery of entire piece of the system and serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers. You will do everything from determining priorities and designing features to re-architecture as necessary, automated testing and mentoring others. The best candidates show true end-to-end ownership.
At SageMaker, there are immense learning as well as growth opportunities. This is a great team to come to have a huge impact on AWS and the world's customers we serve!
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
Basic Qualifications
· 2+ years of non-internship professional software development experience
· Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
· 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
· Bachelor’s Degree in Computer Science, Computer Engineering or related field
· Solid Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis
Preferred Qualifications
· Experience building 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
· Experience defining system architectures and exploring technical tradeoffs
· Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
· Hands-on expertise in building and operating complex distributed systems
· Master's degree in Computer Science, Computer or Electrical Engineering or related field
· Experience building and operating mission critical, highly available (24x7) systems
· Experience with machine learning, data mining, and/or deep learning frameworks is a plus
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.
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.
Tags: A/B testing Architecture AWS Computer Science Data Mining Deep Learning Distributed Systems Engineering HPC Machine Learning ML models SageMaker Testing
Perks/benefits: Career development Conferences
Region:
North America
Country:
United States
Job stats:
8
1
0
Categories:
Deep Learning Jobs
Engineering Jobs
Machine Learning Jobs
More jobs like this
Explore more AI, ML, Data Science career opportunities
Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
- Open Lead Data Analyst jobs
- Open MLOps Engineer jobs
- Open Data Science Manager jobs
- Open Senior Business Intelligence Analyst jobs
- Open Data Manager jobs
- Open Data Engineer II jobs
- Open Power BI Developer jobs
- Open Principal Data Engineer jobs
- Open Sr Data Engineer jobs
- Open Data Analytics Engineer jobs
- Open Business Intelligence Developer jobs
- Open Junior Data Scientist jobs
- Open Data Scientist II jobs
- Open Product Data Analyst jobs
- Open Senior Data Architect jobs
- Open Sr. Data Scientist jobs
- Open Business Data Analyst jobs
- Open Big Data Engineer jobs
- Open Data Analyst Intern jobs
- Open Manager, Data Engineering jobs
- Open Azure Data Engineer jobs
- Open Data Product Manager jobs
- Open Data Quality Analyst jobs
- Open Junior Data Engineer jobs
- Open Principal Data Scientist jobs
- Open Data quality-related jobs
- Open Business Intelligence-related jobs
- Open GCP-related jobs
- Open ML models-related jobs
- Open Data management-related jobs
- Open Java-related jobs
- Open Privacy-related jobs
- Open Finance-related jobs
- Open Data visualization-related jobs
- Open APIs-related jobs
- Open Deep Learning-related jobs
- Open PyTorch-related jobs
- Open TensorFlow-related jobs
- Open PhD-related jobs
- Open Consulting-related jobs
- Open Snowflake-related jobs
- Open NLP-related jobs
- Open CI/CD-related jobs
- Open Kubernetes-related jobs
- Open Data governance-related jobs
- Open Airflow-related jobs
- Open Hadoop-related jobs
- Open LLMs-related jobs
- Open Generative AI-related jobs
- Open Databricks-related jobs