Are you passionate about Artificial Intelligence, Machine Learning and Deep Learning? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI/ML/DL tools on Amazon Web Service (AWS)? Come join us!
At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning (ML), as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our heritage.
Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) API-driven Services like Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with a simple API call.
AWS is looking for a Machine Learning Solutions Architect (ML SA), who will be the Subject Matter Expert (SME) for helping design solutions that leverage our ML services. As part of the team, you will work closely with customers in one or more industry verticals (Financial Services, Media and Entertainment, Manufacturing, Technology, Health Care and Life Sciences, Retail, etc.) to enable large-scale use cases, design ML pipelines, and drive the adoption of AWS for the AI/ML platforms. You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers to fully leverage AI/ML on AWS. Additionally, as the voice of the customer, you will work closely with the service teams, and submit product feature requests to drive the platform forward.
You must have deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. A strong mathematics and statistics background is preferred in addition to experience building complex machine learning models. You will be familiar with the ecosystem of software vendors in the AI/ML space, and will leverage this knowledge to help AWS customers in their selection process.
Roles and Responsibilities
· Working with customers’ development and data science teams to deeply understand their business and technical needs. After understanding their needs, you will design solutions that make the best use of the AWS cloud platform and AWS AI/ML Services including SageMaker, Amazon Comprehend, Amazon Recognition, Amazon Transcribe, Amazon Lex, Amazon Polly, Amazon Forecast, Amazon Personalize, and the other AI/ML services.
· Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and revenue attainment for Amazon SageMaker.
· Thought Leadership – Evangelize AWS ML services and share best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
· Act as a technical liaison between customers and the AWS SageMaker services teams to provide customer driven product improvement feedback.
· Develop and support an AWS internal community of ML related subject matter experts.
Our team puts a high value on work-live balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop and enable them to take on more complex tasks in the future.
· Graduate degree in a highly quantitative field (Computer Science, Machine Learning, Operations Research, Statistics, Mathematics, etc.)
· 5+ years of industry experience in predictive modeling and analysis
· Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relationships
· Consulting experience and track record of helping customers with their AI needs
· Publications or presentation in recognized Machine Learning, Deep Learning and Data Mining journals/conferences ·
· Experience with AWS technologies like SageMaker, Redshift, S3, EC2, Data Pipeline, Kinesis & EMR
· Knowledge of SparkML
· Able to write production level code, which is well-written and explainable
· Experience using ML libraries, such as scikit-learn, caret, mlr, mllib
· Experience working with GPUs to develop models
· Experience handling terabyte size datasets
· Track record of diving into data to discover hidden patterns
· Familiarity with using data visualization tools
· Knowledge and experience of writing and tuning SQL
· Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format
· Experience giving public presentations
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Amazon is committed to providing accommodations at all stages through recruitment and employment in accordance with applicable human rights and accommodation legislation. If contacted for an employment opportunity, advise Human Resources if you require accommodation, including in order to apply for a position.
· 3+ years of experience in design/implementation/consulting for Machine Learning/AI/Deep Learning solutions
· 1+ years of experience with one or more Deep Learning frameworks such as Apache MXNet, TensorFlow, Caffe2, Keras, Microsoft Cognitive Toolkit, Torch and Theano
· 5+ years professional experience in software development in languages related to ML like Python or R. Experience working with RESTful API and general service-oriented architectures.
· 3+ years of experience in technical architecture, design, deployment and operations for AI platforms, standards, protocols and devices