Are you passionate about Artificial Intelligence and Machine Learning? Are you passionate about helping Public Sector customers build solutions for a broad range of complex problems? 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; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. Machine learning is a big part of our heritage, and we have thousands of engineers at Amazon committed to advancing the field.
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 Public Sector customers design solutions that leverage our ML services. As part of the team, you will work closely with customers in one or more industry verticals (Education, Federal Government, Non-Governmental Organizations, 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 and machine learning. 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.
If you are a qualified and accepted candidate, you may work out of any of the following cities: Eastern Time Zone - Boston, New York, Washington DC Metro/Dulles, Atlanta; Central Time Zone - Chicago, Dallas, Austin, Nashville; Pacific Time Zone - Southern California (i.e. south of San Diego to north of Los Angeles), Bay Area California, Minneapolis, Seattle, or Portland, Oregon. Travel up to 50% across the AMERICAs may be possible.
Key job 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 Rekognition, Amazon Transcribe, 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 in the Public Sector 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 in the Public Sector.
- 3+ years of design, implementation, or consulting experience in applications or infrastructures
- 8+ years within specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics)
- 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 and/or deploying ML models to production
- Graduate degree in a related field (Computer Science, Machine Learning, Operations Research, Statistics, Mathematics, etc.)
- 5+ years of industry experience in predictive modeling and analysis
- Hands-on experience deploying and managing models at scale, including governance and security
- Consulting experience and track record of helping customers with their AI needs
- 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 working with GPUs to develop models
- Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format
- Experience giving public presentations
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).
The pay range for this position in Colorado is $153,600- 207,800/yr; however, base pay offered may vary depending on job-related knowledge, skills, and experience. A sign-on bonus and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. This information is provided per the Colorado Equal Pay Act. Base pay information is based on market location. Applicants should apply via Amazon's internal or external careers site.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.