Job summary
Job post source
This job is directly from Amazon Web Services (AWS)
Job overview
The Applied Scientist role at AWS Professional Services involves applying AI/ML solutions to solve real-world business problems, working closely with customers to implement and optimize these technologies for significant impact.
Responsibilities and impact
The role requires implementing end-to-end AI/ML and generative AI projects, collaborating with scientists and engineers to develop algorithms, directly interacting with customers to understand and address business needs, and providing best practice guidance and feedback to product teams.
Compensation and benefits
The base salary ranges from $136,000 to $223,400 depending on geographic location and experience, with potential equity, sign-on bonuses, and a full range of medical, financial, and other benefits.
Experience and skills
Candidates must have experience building machine learning models, expertise in algorithms, optimization, and deep learning architectures, hands-on experience with transformer models, and a PhD or equivalent experience; preferred qualifications include deep learning, computer vision, AI agent design, AWS AI services, and strong communication skills.
Career development
AWS offers mentorship, knowledge-sharing, and career advancement resources to help employees grow into well-rounded professionals.
Work environment and culture
AWS promotes an inclusive, diverse, and flexible work environment valuing work-life balance and continuous learning through employee-led affinity groups and ongoing events.
Company information
Amazon Web Services is a leading cloud platform known for innovation and serving a wide range of customers from startups to Global 500 companies.
Team overview
The team consists of scientists, engineers, and architects working collaboratively to build custom AI solutions for customers, focusing on impactful and scalable AI applications.
Job location and travel
The position may require travel to customer sites and offers a flexible work environment, with location specifics depending on the candidate's market.
Application process
Applicants should apply via AWS's internal or external career site; the position remains open until filled, with accommodations available for candidates with disabilities.
Unique job features
This role is distinguished by its customer-facing nature, involvement in cutting-edge AI/ML and generative AI projects, and the opportunity to influence product direction through customer feedback.
Company overview
Amazon Web Services (AWS) is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments on a metered pay-as-you-go basis. AWS generates revenue through a variety of services including computing power, storage options, and networking capabilities, catering to a wide range of industries. Launched in 2006, AWS has become a leader in the cloud services market, known for its innovation and extensive global infrastructure. Key historical milestones include the introduction of Amazon S3 and EC2, which revolutionized cloud storage and computing.
How to land this job
Position your resume to emphasize your experience in building and deploying machine learning models, particularly with transformer and generative AI models, reflecting the end-to-end AI/ML project ownership highlighted in the job description.
Highlight your skills in collaborating with cross-functional teams including AI/ML scientists, engineers, and architects, and your ability to communicate complex technical concepts to business and executive stakeholders, as these are key responsibilities for this role.
Apply through multiple channels such as the Amazon Web Services corporate careers site and LinkedIn to increase your chances of visibility and consideration for the Applied Scientist role.
Connect on LinkedIn with current Applied Scientists and AI/ML professionals within AWS Professional Services; initiate conversations by referencing recent AWS AI innovations, asking for advice on successfully navigating the application process, or expressing enthusiasm about the impact of AWS AI solutions on real-world business problems.
Optimize your resume for ATS by incorporating keywords from the job description such as 'transformer models', 'generative AI', 'Amazon SageMaker', 'machine learning deployment', and 'AI/ML solution implementation' to ensure it passes automated screening effectively.
Use Jennie Johnson's Power Apply feature to automate and tailor your applications across multiple platforms, identify relevant LinkedIn contacts for networking, and optimize your resume for ATS, allowing you to focus your time on preparing for interviews and deepening your AI/ML expertise.
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