Machine Learning Engineer, GenAI, Amazon Connect
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Job Location:
Seattle, OR - USA
Monthly Salary:
Not Disclosed
Posted on:
Yesterday
Vacancies:
1 Vacancy
Department:
Job Summary
As part of the AWS Applied AI Solutions organization we have a vision to provide business applications leveraging Amazons unique experience and expertise that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazons real-world experience to build opinionated turnkey solutions. Where customers prefer to buy over build we become their trusted partner with solutions that are no-brainers to buy and easy to use.
Amazon Connect is an AI-powered customer experience solution that enables superior outcomes at a lower cost. Since its 2017 public launch Amazon Connect has become an AI leader transforming how organizations of all types interact with their customers.
Do you want to build and optimize the infrastructure that serves frontier Large Language Models (LLMs) at massive scale transforming how customers interact with AI-powered services Join a world-class team of ML engineers and scientists within AWS to develop production ML systems that power next-generation applications in cloud computing.
Amazon Web Services (AWS) is the worlds leading cloud platform supporting millions of customers globally. Our customers bring complex high-impact problems that create unique opportunities for Machine Learning Engineers to deliver solutions with immediate real-world impact. You will operate as a technical leader owning the design and evolution of large-scale ML infrastructure. You will partner closely with applied scientists software engineers and product teams to translate frontier LLM research into highly reliable efficient and scalable production systems. You will work with state-of-the-art GPU and custom accelerator hardware and leverage AWSs unmatched scale in data and compute to push the boundaries of LLM serving and optimization.
As part of the team we expect that you will design and build highly available cost-efficient LLM serving systems optimize inference performance across the full stack and develop innovative ML infrastructure solutions that enable our scientists to iterate faster and our customers to experience AI capabilities at their best.
Key job responsibilities
Our machine learning engineers collaborate across diverse teams projects and environments to have a firsthand impact on our global customer base. Youll bring a passion for innovation large language models inference optimization distributed systems and cloud-native ML infrastructure. Youll also:
* Design develop and research machine learning systems end-to-end building robust ML solutions that translate data science prototypes into production-ready systems that drive real business outcomes.
* Build host and maintain production-grade LLM serving and inference infrastructure delivering high-quality highly available always-on AI systems that customers and internal teams can depend on.
* Optimize the full inference stack for performance and cost-efficiency applying techniques such as model quantization batching strategies KV-cache management and accelerator tuning.
* Partner with cross-functional teams and customers to deeply understand real-world challenges and iteratively translate requirements into scalable secure and cost-effective machine learning solutions on AWS.
About the team
Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS its in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences including our Conversations on Race and Ethnicity (CORE) inspire us to never stop embracing our uniqueness.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home theres nothing we cant achieve in the cloud.
Mentorship and Career Growth
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.
- 5 years of non-internship professional software development experience
- 5 years of programming with at least one software programming language experience
- 5 years of leading design or architecture (design patterns reliability and scaling) of new and existing systems experience
- Experience as a mentor tech lead or leading an engineering team
- Knowledge of Machine Learning and LLM fundamentals including transformer architecture training/inference lifecycles and optimization techniques
- Bachelors degree in computer science or equivalent
- 5 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Experience in developing and deploying LLMs in production on GPUs Neuron TPU or other AI acceleration hardware
- Experience with CUDA kernels or ML/low-level kernels
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Amazon Connect is an AI-powered customer experience solution that enables superior outcomes at a lower cost. Since its 2017 public launch Amazon Connect has become an AI leader transforming how organizations of all types interact with their customers.
Do you want to build and optimize the infrastructure that serves frontier Large Language Models (LLMs) at massive scale transforming how customers interact with AI-powered services Join a world-class team of ML engineers and scientists within AWS to develop production ML systems that power next-generation applications in cloud computing.
Amazon Web Services (AWS) is the worlds leading cloud platform supporting millions of customers globally. Our customers bring complex high-impact problems that create unique opportunities for Machine Learning Engineers to deliver solutions with immediate real-world impact. You will operate as a technical leader owning the design and evolution of large-scale ML infrastructure. You will partner closely with applied scientists software engineers and product teams to translate frontier LLM research into highly reliable efficient and scalable production systems. You will work with state-of-the-art GPU and custom accelerator hardware and leverage AWSs unmatched scale in data and compute to push the boundaries of LLM serving and optimization.
As part of the team we expect that you will design and build highly available cost-efficient LLM serving systems optimize inference performance across the full stack and develop innovative ML infrastructure solutions that enable our scientists to iterate faster and our customers to experience AI capabilities at their best.
Key job responsibilities
Our machine learning engineers collaborate across diverse teams projects and environments to have a firsthand impact on our global customer base. Youll bring a passion for innovation large language models inference optimization distributed systems and cloud-native ML infrastructure. Youll also:
* Design develop and research machine learning systems end-to-end building robust ML solutions that translate data science prototypes into production-ready systems that drive real business outcomes.
* Build host and maintain production-grade LLM serving and inference infrastructure delivering high-quality highly available always-on AI systems that customers and internal teams can depend on.
* Optimize the full inference stack for performance and cost-efficiency applying techniques such as model quantization batching strategies KV-cache management and accelerator tuning.
* Partner with cross-functional teams and customers to deeply understand real-world challenges and iteratively translate requirements into scalable secure and cost-effective machine learning solutions on AWS.
About the team
Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS its in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences including our Conversations on Race and Ethnicity (CORE) inspire us to never stop embracing our uniqueness.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home theres nothing we cant achieve in the cloud.
Mentorship and Career Growth
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.
- 5 years of non-internship professional software development experience
- 5 years of programming with at least one software programming language experience
- 5 years of leading design or architecture (design patterns reliability and scaling) of new and existing systems experience
- Experience as a mentor tech lead or leading an engineering team
- Knowledge of Machine Learning and LLM fundamentals including transformer architecture training/inference lifecycles and optimization techniques
- Bachelors degree in computer science or equivalent
- 5 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Experience in developing and deploying LLMs in production on GPUs Neuron TPU or other AI acceleration hardware
- Experience with CUDA kernels or ML/low-level kernels
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Seattle - 168100.00 - 227400.00 USD annually
Required Experience:
IC
Key Skills
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