AmazonPosted 1mo ago

Data Scientist, Automated Vehicle Testing

Data Scientist, Automated Vehicle Testing at Amazon scores 87 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

US, WA, Redmondmidfull-time$136k-$184k

AI in this role

fine-tuning

Amazon Leo is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity.

Export Control Requirement:
Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

We are looking for an experienced Data Scientist to help architect state-of-the-art test infrastructure and lead the development of data models and analysis tools to represent the ground truth about satellite test results in order to facilitate important business decisions. Our team is responsible for core infrastructure and tools that will serve as the backbone of automated satellite testing operations to enable rapid scaling of manufacturing processes.

Key job responsibilities
* Work with engineering, software and manufacturing teams to understand drivers, impacts, and key influences on satellite performance
* Lead the design, build and implementation of production models and make decisions in real time for satellite test results
* Drive actions at scale to optimize test methodology and drive increases to satellite reliability
* Analysis and modeling of satellite telemetry from test results in lab and on-orbit
* Develop models and data pipelines for satellite telemetry
* Create and manage datasets for continued pre-training and supervised fine-tuning of LLMs
* Develop scalable visualizations for analysis of satellite performance

A day in the life
As Amazon Leo Data Scientist you will own the architecture definition and development of data analysis tools to to aid engineering and production teams in deciding flight-worthiness of each Amazon Leo satellite and historical traceability tools to enable simplified discovery and interpretation of past test data. You will work with multiple engineering, software and manufacturing teams across ground and space systems, to specify requirements, define data collection, interpretation strategies, data pipelines and implement data analysis and reporting tools for Integrated Vehicle tests. Your focus will be in optimizing the analysis of test results to enable Amazon Leo production plans.

About the team
The Automated Vehicle Testing Team is a mix of scientists and software engineers responsible for data infrastructure, tools, and research that serve as the backbone of automated satellite testing operations to enable rapid scaling of manufacturing processes.

Basic qualifications

- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 1+ years of working with or evaluating AI systems experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Experience applying theoretical models in an applied environment

Preferred qualifications

- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience working on multi-team, cross-disciplinary projects
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, REDMOND - 136,000.00 - 184,000.00 USD annually

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Fine Tuning

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Fine Tuning. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

Want your resume actually rewritten for this job?

The free preview above is everything we have today. A full resume rewrite is not live yet and has no price set. Join the waitlist and we will email you if we open it.