Thinking Machines LabRemote · San Francisco$350k-$475k5h ago
AmazonPosted 2mo ago
Senior Applied Scientist, International Machine Learning at Amazon scores 94 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.
AI in this role
If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you.
Major responsibilities
- Use machine learning and analytical techniques to create scalable solutions for business problems
- Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes
- Design, development, evaluate and deploy innovative and highly scalable models for predictive learning
- Research and implement novel machine learning and statistical approaches
- Work closely with software engineering teams to drive real-time model implementations and new feature creations
- Work closely with business owners and operations staff to optimize various business operations
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
- Mentor other scientists and engineers in the use of ML techniques
Key job responsibilities
Use machine learning and analytical techniques to create scalable solutions for business problems
Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes
Design, develop, evaluate and deploy, innovative and highly scalable ML models
Work closely with software engineering teams to drive real-time model implementations
Work closely with business partners to identify problems and propose machine learning solutions
Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance
Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production
Leading projects and mentoring other scientists, engineers in the use of ML techniques
About the team
International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide
Basic qualifications
- 7+ years of building machine learning models for business application experience
- PhD, or Master's degree
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
Preferred qualifications
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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.
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
Questions you could be asked
- What's a project where you used TensorFlow hands-on?
- Walk me through how you've used scikit-learn in your day-to-day work.
- 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: TensorFlow and scikit-learn. 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.
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