A

Amazon

Sells products online and rents cloud computing

Delivery Consultant-AI/ML - WWPS Proserve Delivery Team

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 2 years of cloud architecture and solution implementation experience.
  • At least 3 years of experience with machine learning or statistical modeling data analysis tools and techniques.
  • Experience in professional software engineering and software development life-cycle best practices, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence.
  • Currently possess and maintain an active U.S. Government TS/SCI security clearance.
  • Experience defining and creating benchmarks for assessing generative AI model performance.
  • Knowledge of AWS services, including compute, storage, networking, security, databases, machine learning, and serverless technologies.
  • Experience in performance optimization and cost management for cloud environments.
  • Experience applying quantitative analysis to solve business problems and working on multi-team, cross-disciplinary projects.
  • Experience translating complex technical solutions and data-driven insights into clear, actionable recommendations for technical and non-technical stakeholders.

Responsibilities

  • Design and implement complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, including selecting and fine-tuning appropriate models for specific use cases.
  • Develop and deploy machine learning models and generative AI applications that solve real-world business problems, conduct experiments, and optimize performance at scale.
  • Collaborate with customer stakeholders to identify high-value AI/ML use cases, gather requirements, and propose strategies for implementing machine learning and generative AI solutions.
  • Provide technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently, troubleshoot throughout project delivery, and ensure adherence to best practices.
  • Advise customers on advancements in AI/ML, emerging technologies, and approaches to leveraging diverse data sources for business impact.
  • Share knowledge within the organization through mentoring and training, create reusable AI/ML artifacts, and work with team members to prototype new technologies and evaluate technical feasibility.
  • Help customers scope valuable business use cases, select, train, and fine-tune models, and define paths to address technical or business challenges.
  • Assess customers' current data infrastructure, develop proofs of concept, and propose strategies for implementing AI and generative AI solutions at scale.
  • Design and run experiments, research algorithms, and identify ways to optimize risk, profitability, and customer experience.

Desired Qualifications

  • Experience in performance optimization and cost management for cloud environments.
  • Experience applying quantitative analysis to solve business problems and working on multi-team, cross-disciplinary projects.
  • Experience translating complex technical solutions and data-driven insights into clear, actionable recommendations for technical and non-technical stakeholders.

About the Company

Amazon

Sells products online and rents cloud computing

Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.

Company size
10,001+
Company stage
IPO
Headquarters
Seattle, WA
Founded
1994

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