**principal Sa - Autonomous Computing** Job in Amazon

DESCRIPTION

Are you passionate about developing impactful, novel Machine Learning (ML) technology strategy and taking it to large-scale production? Are you passionate about engaging the AI community (AI researchers, developers building AI products, roboticists making robots that work, data scientists, and innovative entrepreneurs in hot startups and large enterprises)?


Artificial Intelligence (AI) has the potential to transform our society and community for generations. Impacting transportation, mobility, telecommunication, energy, healthcare and insurance, rescue and emergency response, hospitality. Achieving this requires implementing one of the most complex computing systems to-date at unprecedented scale. AWS Autonomous Compute is taking a fresh approach with providing an end-to-end, scalable cloud environment that simplifies the development, scaling and production deployment of AI technology. Including a global cloud footprint, infinitely scalable cloud storage, advanced networking and security, state-of-the-art AI platforms and services, rigorous engineering, and a team with the longest experience building cloud technologies.
AWS Autonomous Computing is seeking a Principal Solutions Architect (SA) for our Autonomous Computing business. The SA will be responsible for defining, building and deploying effective and targeted technology strategy to accelerate broad pre-sales engineering activities. The SA will facilitate the enablement of solutions architecture with specific customer centric value proposition and demos about end-to-end AI technologies data ingestion, data preparation, model development including architecture optimization, model validation, large-scale orchestration, deployment and model lifecycle management on the AWS cloud. The SA will directly interface with the AWS product and software development teams regarding customer and partner requirements. The SA will work closely across multiple internal and external organizations AWS product engineering, business development, sales, marketing, partners, and machine learning research communities to position the AWS platform for customers and partners; and provide guidance on the value proposition and benefit to those customers and partners.

The ideal candidate will possess a deep technical background combined with business acumen that enables them to drive an engagement and interact at the highest levels of startups and large Enterprises. The candidate will have the technical depth and business experience to easily articulate the potential and challenges of AI (different platforms and frameworks in the AWS cloud) to engineering/research teams and C-Level executives. This requires deep familiarity with state-of-the-art approaches to AI, as well as target AI use cases using distributed computing systems in the cloud.



As the ideal candidate, you will be the thought leader responsible for helping customers understand the value proposition of production-grade AI on AWS, creating the most compelling content and demos to help customers understand the use cases and value propositions, and building the right programs to increase awareness and adoption. You will also be a trusted advisor to customers and internal teams; helping develop the AI knowledge and skills of Solutions Architects, as well as the technical field community. Additionally, you will work with the AWS Machine Learning and AWS EC2 engineering and product management teams to shape product vision and prioritize features for AI products and solutions. You will get to work on a leading technology field and growing business; and have a material impact, every day. You will be able to facilitate relationships with senior personnel, as well as easily interact and give guidance to technical experts, researchers, software developers, IT pros, and system architects. This requires a demonstrated ability to think strategically about business, product, research, and technical challenges.

This is an opportunity to be a thought leader in the emerging space of autonomous computing and make a significant contribution to enable transformation across several industries.


About AWS

Amazon Web Services (AWS) is the pioneer and recognized leader in Cloud Computing. Our web services provide a platform for IT infrastructure in-the-cloud that is used by hundreds of thousands of developers and businesses around the world. These customers range from start-ups to leading web companies to Global 2000 companies in financial services, pharmaceuticals, and technology. AWS customers are looking for ways to transform their businesses and solve their own complex business challenges with machine learning (ML) technologies in the cloud. AWS is leading the way in providing customers with powerful, end-to-end machine learning platforms such as Amazon SageMaker.

Roles & Responsibilities:
Architect advanced solutions leveraging AWS services like EC2, S3, SPOT, and ML related services, working closely with our customers to deeply understand their business needs and to design technical solutions that take advantage of the AWS Cloud platform.
Demonstrate the viability of each solution through mechanisms like proof-of-concepts, prototypes and pilots including applied research activities that bring early-stage products to market.
Develop best practices documentation, and develop a strong go-to-market technical strategy.
Craft and develop compelling audience-specific messages and tools (product videos, customer success stories, advanced demos, white papers, presentations, how to guides, etc.)
Evangelize AWS AI architectures and technologies through forums such as AWS Blogs, white papers, reference architectures and public-speaking events such as AWS summit, and user-group events.
Collaborate with AWS field sales, professional services, training and support teams to help partners and customers learn and effectively use AWS for AI.
Serve as a key member of the business development and account management teams helping to ensure customer and partner success in AI on the AWS platform.
Act as a technical liaison between customers, service engineering teams and support teams.
Gain recognition and credibility as a regular panelist and keynote speaker for multiple internal and external events.
Deliver compelling presentations, product demos, roadmap reviews, sample solutions and discussions to drive adoption of AI on AWS.
Identify leads for potential engagement needing pre-sales support.
Collaborate with internal teams to define the product road map, market positioning and developer program initiatives
Assess training requirements and coordinating with various training teams on scheduling and delivery of training to both internal and external audiences.

BASIC QUALIFICATIONS

- MS in Engineering (or related STEM fields)
- 7+ years experience working with a few of these technologies: advanced machine learning, probabilistic modeling, optimization, sensor fusion and scalable computing systems.
- Demonstrated ability to work with multiple technical and stakeholder groups to bring a complete solution to production.
- Strong track record of publications in peer-reviewed journals, conferences and/or curated blogs.
- Deep knowledge and extensive experience building and deploying one or more of these technologies in production: Deep learning (e.g. CNN, RNN, LSTM, GAN, etc.), Reinforcement Learning, Accelerated compute (e.g. GPU, FPGA, ASICs, etc.), ML Frameworks (e.g. TensorFlow, PyTorch, etc.), ML engineering (e.g. Containers, Kubernetes, Kubeflow, etc.), Probabilistic Modeling (e.g. Bayesian modeling, Probabilistic Deep Neural Networks, Probabilistic Graphical Models, etc.), Global non-convex optimization (e.g. Genetic Algorithms, Particle Swarm, etc.) and non-linear estimation techniques (e.g. Unscented Kalman Filters, Particle filters, etc.) and time series forecasting.

- Experience with one or more general purpose programming languages, including but not limited to: Python, Go, C/C++, JavaScript, Java.
- Solid enterprise communication skills, and business and financial acumen.
- Strong analytical skills, and demonstrated ability to turn detailed data analysis into useful strategic insight in order to drive customer adoption and make appropriate recommendations to the business.
- Strong verbal and written communications skills are a must, as well as leadership skills.
- Demonstrated ability to work effectively across internal and external organizations.

PREFERRED QUALIFICATIONS

- Ph.D. in Engineering (or related STEM fields)
- Experience developing, deploying and managing AI products at scale.
- 10+ years of engineering, development, data science and modeling experience.
- Demonstrated experience solving end-to-end large-scale problems in aerospace, transportation, energy, manufacturing, telecommunications, genomics, healthcare and/or robotics with proven AI technologies deployed at scale.
- Experience with cloud computing and distributed computing.

Amazon.com is an Equal Opportunity-Affirmative Action Employer Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation/ Age.