$122900 - $130900 Year
Monday to Friday
Others
Day shift
8 hour shift
Others
Health insurance
Paid time off
Dental insurance
Vision insurance
401(k)
Parental Leave
Others
Key job responsibilities
- Work with customer’s AI team to deeply understand their business and technical needs and build AI solutions that make the best use of the AWS Cloud platform and AI Services.
- Thought Leadership – Evangelize AWS 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.
- Partner with Generalist SAs, Sales, Business Development and the AI Service teams to accelerate customer adoption and revenue attainment.
- Act as a technical liaison between customers and the service engineering teams and providing produce improvement feedback.
- Develop and support an AWS internal community of AI related subject matter experts.
- In partnership with the sales team, formulate and execute a sales strategy to exceed Global Life Sciences (GLS) revenue objectives through the adoption of AWS
- As a key member of the GLS business development and sales team, ensure success in building and migrating applications, software and services on the AWS platform
- Educate GLS customers on the value proposition of AWS, and participate in deep architectural discussions to ensure solutions are designed for successful deployment in the cloud
- Conduct one-to-few and one-to-many training sessions to transfer knowledge to customers considering or already using AWS
- Capture and share best-practice knowledge amongst the AWS solutions architect community
- Author or otherwise contribute to AWS customer-facing publications such as whitepapers
- Build deep relationships with senior technical individuals within customers to enable them to be cloud advocates
- Act as a technical liaison between customers, service engineering teams and support
BASIC QUALIFICATIONS
- 5+ years in machine learning model development lifecycle including (but not limited to) training, fine tuning feature engineering techniques and deployment options
- 5+ years of Hands-on experience with python, R or other programming languages and independently building prototype applications
- 5+ years experience building with libraries like PyTorch, Tensorflow, MxNet and ScikitLearn
- 6+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 3+ years of design, implementation, or consulting in a customer facing role
- 7+ years of IT development or implementation/consulting in the software or Internet industries experience
PREFERRED QUALIFICATIONS
- Deep understanding of neural networks like transformers and the ability to customize them based on a dataset and problem statement.
- 5+ years of infrastructure architecture, database architecture and networking experience
- Experience working with end user or developer communities
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.
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