Machine Learning Engineer II, Workforce Solutions
Seattle, WA, USA
Full Time Mid-level / Intermediate USD 115K - 223K
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...As a member of our team, you'll work on cutting-edge projects that directly impact over a million Amazon associates. This role will provide exposure to state-of-the-art innovations in AI/ML systems (including GenAI). Technologies you will have exposure to, and/or will work with, include AWS Bedrock, Amazon Q, SageMaker, and Foundational Models such as Anthropic’s Claude / Mistral, among others.
The types of initiatives you can expect to work but not limited to include:
- Developing personalized recommendation systems.
- Building AI Assistant tools that have cross-Amazon user adoption.
Key job responsibilities
- Design, implement, and productionize AI/ML models by working very closely with scientists on the team.
- Develop ML/LLM workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure a high bar for the quality of architecture and design of our AI ML systems and data infrastructure
- Leverage AWS AI services and other internal / publicly available external tools & services to accelerate our AI investments
- Detail-oriented, always backs up ideas with facts. Understands complex application data flows and bridge the gap between technical and business app requirement
- Identify state of the art models / solutions to enable new capabilities for code migration and code testing, drive down tech debt and increase operational efficiency
- Share expert knowledge in performance, large scale distributed system scalability, system architecture, and engineering best practices
- Provide thought leadership and hands-on support in selecting, defining, training and fine-tuning Large Language Models (LLMs), prompt engineering, and other GenAI efforts.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA | Austin, TX, USA | Bellevue, WA, USA | Nashville, TN, USA | Phoenix, AZ, USA | Seattle, WA, USA | Tempe, AZ, USA
Basic Qualifications
- 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
- 1+ years of non-internship experience in machine learning
Preferred Qualifications
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience- Bachelor's degree in computer science or equivalent
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 $115,000/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.
Tags: Anthropic Architecture AWS Claude Computer Science Engineering Generative AI LLMs Machine Learning ML models Pipelines Prompt engineering SageMaker SDLC Testing
Perks/benefits: Career development Equity / stock options
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