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Urgent! Sr. Applied AI - Data Scientist, Amazon Nova Job Opening In Boston – Now Hiring Amazon
Description
Are you a AI-focused data scientist that wants to think fast, dive deep, and build?
We are seeking a data scientists to join our the Amazon Nova Solutions team to work with Foundation Model (FM) teams alongside internal and external Generative AI customers to customize foundation models and build the applications of the future.
In this role, you will be the voice of the builder, with ownership for working alongside Amazon businesses to develop GenAI solutions that deliver their immediate business value and realize the future of customer experience.
You will help your customers understand best practices and develop new best-practice patterns as you encounter new problem spaces.
With your day to day focus on the builder, you will be expected to provide insights to product, science, and engineering on how customers build with our FM's and how we can improve.
You will be empowered to invent on behalf of our customers and advocate for their needs throughout design, build, and launch of next gen FM's.
You must have deep technical experience working with technologies related to large language models including LLM architectures, model evaluation, and fine-tuning techniques.
You should be proficient with design, deployment, and evaluation of foundation models - including evaluation dataset design, metric design, implementation, failure analysis.
Ideal candidate has hands on experience with both AI Frameworks (e.g. Strands, LangGraph, CrewAI, DSPy) and model customization tools including PyTorch, TensorBoard, MLFlow/W&B, Bedrock, and SageMaker
This position has a high level of visibility, so you will need to be able to communicate clearly and compellingly at all levels of the company.
Additionally, you will be responsible for measuring business impact by diving deep into metrics and customer inputs.
You should have a positive attitude and strong work ethic; you will work fast and smart, and adapt and iterate quickly.
Key job responsibilities
- Customer Advisor- Implement, and deploy state of the art machine learning solutions under Gen AI.
You will build prototypes, PoCs, and explore new solutions.
You will interact closely with our customers.
- Thought Leadership – Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
- Ensure success in designing, building and migrating applications, software, and services with Amazon Nova FM's, AWS Bedrock, and other AWS GenAI capabilities.
- Interact with customers directly to understand their business problems and help them implement durable GenAI systems.
- Educate customers on the value proposition of amazon Nova FM ecosystem and showcase the art of possible.
- Drive evaluation strategy, metric design, and evaluation data design for real-world use cases
- Drive deep architectural discussions and design exercises to create solutions built with Amazon Nova FM's
- Author and contribute to AWS customer-facing publications such as whitepapers, workshops, demos and proof of concepts.
- Build deep relationships with customer engineering, product, and science leaders.
About the team
Amazon Nova Applied AI Solutions Team serves as a bridge between Foundation Model science, engineering, and product teams and the internal Amazon teams using these models to deliver business value to Amazon's customers.
We help customers build GenerativeAI applications and apply the learning from these engagemetns to help make the Foundation Models better every day.
Basic Qualifications
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, engineering, or computer science.
- 5+ years of experience in end to end technical architecture, design, deployment and operations for Generative AI/ML platforms and applications.
- 3+ year experience working with technologies related to large language models including LLM architectures and model evaluation
- Experience in design/implementation/consulting for Machine Learning/AI/Deep Learning solutions
- Experienced in specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience.
Preferred Qualifications
- Experience with optimizing ML workloads using Model compression, distillation, pruning, sparsification, quantization, Transformers based algorithms like FlashAttention, PagedAttention, Speculative decoding, Distributed training/inference optimization, Hardware-informed efficient model architecture.
- Experience with open source frameworks for building applications powered by language models like LangChain, LlamaIndex.
Design, develop, and optimize high-quality prompts and templates that guide the behavior and responses of LLM.
- Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approachesCustomer facing skills to represent AWS well within the customer’s environment and drive discussions with senior personnel regarding trade-offs, best practices, and risk mitigation.
- Experience with AWS technologies like SageMaker, Step Functions, OpenSearch, PgVector, S3, IAM, Cognito, EC2, Glue, & EMR.
- Experience with Container Platforms (Docker, Kubernetes/Fargate).
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies.
Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position.
These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation.
Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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 $143,300/year in our lowest geographic market up to $247,600/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.
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Unlock Your Sr Applied Potential: Insight & Career Growth Guide
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Great news! Amazon is currently hiring and seeking a Sr. Applied AI Data Scientist, Amazon Nova to join their team. Feel free to download the job details.
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