Applied Scientist, AWS Professional Services

Profile insights
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Skills

TensorFlow

Software deployment

PyTorch
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Education

Doctoral degree

Master's degree

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Job details
Here’s how the job details align with your profile.
Pay

$136,000 - $223,400 a year
 
Full job description
DESCRIPTION

Are you looking to work at the forefront of Machine Learning (ML) and Artificial Intelligence (AI)? Would you be excited to apply AI algorithms to solve real world problems with significant impact? The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Applied Scientist to help customers implement AI/ML solutions and realize transformational business opportunities.

This is a team of scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine-tune the right models, define paths to navigate technical or business challenges, develop scalable solutions and applications, and launch them in production. The team provides guidance and implements best practices for applying AI responsibly and cost efficiently.

You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

We’re looking for Applied Scientists capable of using AI/ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.



Key job responsibilities
As an experienced Applied Scientist, you will be responsible for:

1. Implement end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, solution deployment, and post-production monitoring
2. Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate generative AI algorithms and build ML systems to address real-world challenges
3. Interact with customers directly to understand the business problem, help and aid them in implementation of AI/ML solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production
4. Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholder.
5. Provide customer and market feedback to product and engineering teams to help define product direction
This is a customer-facing role with potential travel to customer sites as needed.

About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture - Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth - We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

BASIC QUALIFICATIONS

Experience with building machine learning models for business application experience
Experience in any of the following areas: algorithms and data structures, optimization, parallel and distributed computing, deep learning architecture, high-performance computing
Experience with hands-on experience with training, fine-tuning, devaluating, and deploying transformer models in production
PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field, or Masters degree plus 5 years of relevant work experience
Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies
PREFERRED QUALIFICATIONS

Experience with deep learning, computer vision, human robotic interaction, algorithms implementation experience using PyTorch and TensorFlow
Experience with design, deployment, and evaluation of AI agents and orchestration approaches; experience with open source frameworks like LangChain, LlamaIndex, and/ or similar tools
Experience building AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

Job details

USA, MA, Boston
USA, TX, Austin
USA, WA, Seattle
USA, VA, Arlington
USA, GA, Atlanta
USA, NY, New York
USA, IL, Chicago
USA, TX, Dallas
USA, Mountain View
Machine Learning Science