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About the role

AI/ML Consultant, AWS Professional Services at Amazon Web Services Australia Pty Ltd - D81

Required Skills

machine learninggenerative aiawspythonpytorchtransformersdockergitsagemaker

About the Role

The AI/ML Consultant at AWS Professional Services helps major global companies develop and implement machine learning and generative AI solutions using AWS services. They work with customers to understand business challenges, design and build ML/GenAI solutions, and collaborate with technical teams to bring solutions to production.

Key Responsibilities

  • Understand customer business challenges and structure them as requirements
  • Select AI/ML services and algorithms, and build/verify ML solutions with technical specialists
  • Assist customers in developing ML/GenAI projects from start to finish, including technical sales support and deployment
  • Collaborate with ML Engineers, Cloud Architects, and Application Developers to build production-ready solutions
  • Work with AWS services (e.g., Amazon Bedrock, SageMaker), Git, Docker, and ML/GenAI frameworks

Required Skills & Qualifications

Must Have:

  • Bachelor’s degree or equivalent in computer science, machine learning, operations research, statistics, or mathematics
  • Experience as a machine learning engineer or data scientist building ML models and prompting GenAI models
  • Strong communication skills to work collaboratively with clients and teams
  • Experience with AWS or similar cloud technologies

Nice to Have:

  • Master's degree in computer science, machine learning, operations research, statistics, mathematics, or related fields
  • Deep technical skills and business savvy to collaborate with executives and engineers
  • Skills in creating experimental and analytical plans for data modeling and determining cause-and-effect relationships
  • Experience consulting with customers on AI and GenAI needs

Benefits & Perks

  • Inclusive team culture with affinity groups and inclusion events
  • Mentorship and career growth opportunities with knowledge-sharing resources
  • Work-life balance with flexibility as part of the working culture