Specialist SA, Artificial Intelligence / Machine Learning (AI/ML)
DESCRIPTION As a Specialist ML Solutions Architect at AWS, you'll build technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey in adopting Machine Learning across their organisation.
You'll manage the overall technical relationship, for Machine Learning related projects, between AWS and our customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate their projects.
Internally, you will be the voice of the customer, sharing their needs and wants to inform the roadmap of AWS AI/ML features.
In this role, your creativity will link technology to tangible solutions, with the opportunity to define or invent cloud-native Machine Learning reference architectures for a variety of use cases.
You will participate in the creation and sharing of best practices, technical content and new reference architectures (e.g. white papers, code samples, blog posts) and evangelize about running Machine Learning workloads on AWS and industry ML trends (e.g. through workshops, user groups, meetups, public speaking, online videos or conferences).
If you can educate AWS customers about the art of the possible, while challenging the impossible, come build the future with us.
BASIC QUALIFICATIONS • Experience in the field of AI, Machine Learning, Deep Learning and related technologies.
• Data science background and experience manipulating/transforming data, model selection, model training, cross-validation and deployment at scale.
• Experience with Machine and Deep Learning toolkits such as PyTorch, Scikit-learn, XGBoost, MXNet & TensorFlow
• Experience with software development and developing production-grade code. Experience working with RESTful API and general service oriented architectures.
PREFERRED QUALIFICATIONS • Academic background in Mathematics, Computer Science, Statistics or equivalent professional experience
• Experience communicating effectively across internal and external organizations, for complex mission-critical solutions
• Experience with predictive analytics, semi- and unstructured data
• Experience deploying production-grade machine learning solutions on public cloud platforms
• Experience with AWS (or comparable) services adjacent to AI/ML, particularly Amazon EMR, Amazon S3, AWS Lambda, AWS IoT Core & Greengrass, Amazon DynamoDB, Kubernetes, Amazon EC2 Container Service, AWS IoT Greengrass etc.
• Experience influencing and building mindshare convincingly with any audience.
• Confident and experienced in speaking to large audiences.