AI/ML Consultant, AWS Professional Services

AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You'll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.

Are you passionate about developing machine learning (ML) and Generative AI (GenAI) solutions? Would you like to help major global companies develop new businesses using ML and GenAI? Do you want to help to develop enterprise use cases using Amazon Web Services (AWS) ML and GenAI services? Amazon has been investing in research and application of ML for decades. We are looking for people who can leverage their machine learning and Generative AI expertise to solve various business problems for our customers.

AWS Professional Services helps AWS customers accelerate the use of ML and GenAI to solve business and operational challenges and drive innovation within their organisations. We are focused on customer obsession and take pride in partnering with our customers to achieve success. If you have experience building ML or GenAI solutions, we encourage you to join us. We are constantly innovating at AWS, and look forward to working with great teammates and helping our customers together.

AI/ML Consultants understand customer business issues, dig deep into relevant data, analyse it, identify the root cause, and summarise solutions. They build these solutions, using ML, GenAI and related AWS ML services as core component to solve the customer issues. They also work with their teammates such as ML Engineers, Application Developers and Cloud Architects to bring the solution to a production ready level. They combine services and related technologies to present optimal solutions to customers and support their realisation. They are passionate about setting innovative goals and providing technical solutions to achieve them. We welcome candidates who are always eager to learn new things and want to innovate together with customers in the world of ML and GenAI.

Key job responsibilities
- Accurately understand the customer's business challenges and needs, structure the problems, and organise them as business requirements.
- Extract the IT requirements necessary to realise the business requirements and select candidate AI/ML services and algorithms. In addition, you will work with specialist roles in related technical fields to build and verify ML solutions, as wellas help develop an architecture that combines the necessary AWS services for achieving the customer's goals.
- Assist our customer on developing ML and GenAI projects from start to finish, providing technical sales support, conducting exploratory data analysis, building and validating ML and/or GenAI solutions, deploying validated solutions on their supporting infrastructure, and providing training to our customers.
- Collaborate with ML Engineers Cloud Architect and Application Developer to build a production ready ML or GenAI solution
- To support the above, you will work with a wide range of IT tools, including AWS services (e.g. Amazon Bedrock, Amazon Sagemaker, Amazon AgentCore), Git and Docker, as well as with a range on Ml and GenAI framework such as Strands-Agents, pytorch, transformers, etc

About the team
Diverse Experiences
AWS 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, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Why AWS?
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's 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
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

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, there's nothing we can't achieve.

Basic Qualifications:
- Bachelor's degree or equivalent experience in fields such as computer science, machine learning, operations research, statistics, or mathematics
- Experience as a machine learning engineer or data scientist with experience building ML model and prompting GenAI model
- Strong communication skills to work collaboratively with clients and related teams across various roles
- Experience with AWS or similar cloud technologies

Preferred Qualifications:
- Master's degree in computer science, machine learning, operations research, statistics, mathematics, or other fields
- Deep technical skills and business savvy, able to collaborate with a wide range of clients, from executives to engineers
- Skills in creating experimental and analytical plans for data modelling processes, and the ability to accurately determine cause-and-effect relationships using baselines.
- Experience consulting with customers (including user departments) on their AI and GenAI needs.

Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.

IDE statement:
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 you're applying in isn't listed, please contact your Recruiting Partner.

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