Deep Learning Solutions Architect - ML Labs
Machine Learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.
The ML team within AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and the cloud. As a Deep Learning Solutions Architect, you'll partner with technology and business teams to build new services that surprise and delight our customers.
You will be working with terabytes of text, images, and other types of data to solve real-world problems.
You will help build well-architected solutions with AWS, and particularly with AI/ML Services, to help customers solve their critical business cases, such as autonomous driving, supply chain optimization, predictive maintenance, fraud detection and more. You will support our customers on their ML journey by helping to develop Proof of Concepts, and at the same time helping them understand the technology behind the scientific choices you make..
We're looking for capable architects and system/software engineers capable of using ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
The primary responsibilities of this role are to:
• Use ML tools, such as Amazon SageMaker and Amazon Simple Storage Service, to provide a scalable cloud environment for our customers to label data, build, train, tune and deploy their models
• Collaborate with our Data Scientists to create and develop scalable ML solutions for business problems
• Interact with customers directly to understand the business problem, help and aid them in implementation of their ML ecosystem
• Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes
• Work closely with account team, research scientist teams and product engineering teams to drive model implementations and new algorithms
This position requires travel of up to 40%.
We at AWS value individual expression, respect different opinions, and work together to create a culture where each of us is able to contribute fully. Our unique backgrounds and perspectives strengthen our ability to achieve Amazon's mission of being Earth's most customer-centric company.
This team will be comprised of Deep Learning Architects and Data Scientists to create cutting edge solutions for clients across EMEA. We are currently recruiting for talented individuals in the following cities: London and Berlin. Discover more at https://www.amazon.jobs/en/teams/amazonai. BASIC QUALIFICATIONS
• Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
• Several years of relevant experience in building large scale enterprise IT systems in a production environment
• Experience coding in Python, R, Matlab, Java or other modern programming language
• At least 1 year of public cloud computing experience in AWS or other large scale cloud provider
• At least 1 year of experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences)
• Fluency in written and spoken English PREFERRED QUALIFICATIONS
• Masters or PhD degree in Computer Science, or related technical, math, or scientific field
• Strong working knowledge of deep learning, machine learning and statistics
• Hands on experience building models with deep learning frameworks like MXNet, Tensorflow, Caffe, Torch, Theano or similar.
• Hands on experience with deep learning (e.g., CNN, RNN, LSTM)
• Fluency with other European languages are a plus
• Strong communication and data presentation skills
• The motivation to achieve results in a fast-paced environment.
• Experience with statistical modelling / machine learning
• Strong attention to detail
• Comfortable working in a fast paced, highly collaborative, dynamic work environment
• Ability to think creatively and solve problem