Specialist Solutions Architect - Machine Learning/Forecast

Seattle, Washington, USA

Full Time
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Posted 2 weeks ago

This position can be remote, but candidates must be based near an AWS office location (Arlington, Atlanta, Austin, Boston, Chicago, Cupertino, Dallas, Denver, East Palo Alto, Herndon, Houston, Irvine, Minneapolis, New York City, Portland, San Diego, San Francisco, Washington D.C., Sunnyvale, Santa Monica, Seattle).

Do you enjoy working with data to help customers optimize processes using Machine Learning? Have you spent hours putting an analysis together and challenged key parameters only to see if they matter? Have you debated using percentage errors or root mean square errors? Or precision at 5 Vs. precision at 30? Come work with us!

As a Specialist Solutions Architect, you will continuously sharpen your knowledge around the end-to-end model development lifecycle from data preparation and feature engineering to model development and retraining. You will use your expertise to guide customers how to operate ML solutions.
As a trusted advisor for AI/ML, you will share recommendations around security, cost, performance, reliability and operational efficiency to accelerate innovative and mission-critical projects our customers are building.
Internally, you will be the voice of the customer. You will articulate customer needs by synthesizing your observations from customer engagements and market trends around ML workloads to inform the roadmap of AWS features.
You will lead the creation and sharing of best practices, technical content and new reference architectures (e.g. white papers, code samples, blog posts) and evangelize and educate about AWS technology and industry trends in the AI/ML space using public speaking and content engagements like workshops, user group meetings, online videos, and conferences.

If you like talking about about the art of the possible, while challenging the impossible, come build the future with us.

· Work with customers’ data science & development teams along with business stakeholders to understand their optimization needs.
· Design working prototypes, reference examples, proofs of concept that make the best use of AWS offerings like Amazon Personalize, Amazon Forecast, and Amazon SageMaker.
· Produce and validate reference architecture implementations, CloudFormation templates, and blog posts to evangelize design patterns and best practices for applying AWS AI and ML services to help customers in different vertical segments like consumer packaged goods, retail, manufacturing, healthcare, and life sciences.
· Act as a technical liaison between customers and the AWS product teams to provide customer driven product improvement feedback.
· This is a customer facing role. You will be required to travel to meet customers when needed (and it is safe to do so).

Basic Qualifications

· Bachelor’s degree in Computer Science, Engineering, Mathematics or a related field or equivalent professional or military experience
· 2+ experience working with customers in industries such as Manufacturing, Retail, Wholesale, CPG, Pharmaceuticals, Life Sciences, Service Parts Planning on their fulfillment based operational processes
· Ability to engage business users on value-based process improvement discussions in addition to engaging data science and IT organizations internally and externally
· Over a year of experience in design/implementation/consulting for Machine Learning/AI/Deep Learning solutions
· Experience working with, at least, one modern programming language such as Python, Node.js, Go, Java, .Net, C# along with data querying languages (e.g. SQL, Hadoop/Hive, Scala) and statistical/mathematical software (e.g. R, Matlab, Stata)
· Over a year of experience with one or more Deep Learning frameworks such as Apache MXNet, TensorFlow, Caffe2, Keras, Microsoft Cognitive Toolkit, Torch and Theano
· Strong verbal and written communication skills, with the ability to work effectively across internal and external organizations

Preferred Qualifications

· 5+ years experience with predictive modeling, analysis, and time series forecasting
· Publications or presentation in recognized Machine Learning, Deep Learning and Data Mining journals/conferences
· Proven ability to convey rigorous technical concepts and considerations to non-experts
· Fluency with machine learning on AWS including Amazon SageMaker, Amazon EMR, and related services like Amazon Kinsesis
· Familiarity with software development on AWS including Serverless development experience including complex integrations with AWS Lambda, Amazon Elasticsearch, Amazon Redshift, Amazon Kinesis, and Amazon DynamoDB
· Experience selling to Fortune 1000 and/or Global 2000 organizations

Job tags: AI AWS Consulting Data Mining Deep Learning Engineering Hadoop Healthcare Java Keras Machine Learning Matlab ML MXNet Python R Redshift Scala Security SQL TensorFlow Theano Travel