AI/ML Architect, Public Sector Professional Services

AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and consistent support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow.

Are you passionate about developing machine learning (ML) and Generative AI (GenAI) solutions? 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. 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, analyse them, 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 AI/ML Engineers and Application Developers to bring these solutions to a production ready level. They are passionate about setting innovative goals and providing technical solutions to achieve them.

You will be supporting Canadian Public Sector projects in this role.

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.

A day in the life
AWS Professional 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.

About the team
About AWS: diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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: here at AWS, it’s 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) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

BASIC QUALIFICATIONS

- Experience with AWS or cloud technologies
- Bachelor's degree or above in Engineering, Computer Science, Machine Learning, Operations Research, Statistics, or related work experience
- 5+ years of experience as a data scientist or ML Engineer with experience building ML models and GenAI systems
- Ability to obtain Canadian federal security clearance, or valid Secret or Top Secret clearance.

PREFERRED QUALIFICATIONS

- Experience developing experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
- Deep technical skills and business savvy, able to collaborate with a wide range of clients, from executives to engineers
- Experience consulting with customers (including user departments) on their AI and GenAI needs.
- Experience in building and maintaining MLOps systems, bringing models to production, and running data science development environments.
- Knowledge/experience of data governance principles and practices
- Knowledge/experience of data consumptions, visualization and reporting

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.