Sr Applied Scientist, CreativeX
Amazon is hiring a Sr Applied Scientist, CreativeX in New York, United States. It pays $184k-$249k a year and Level rates it ; you can apply on Level.
Level's read on this job
- On Level's scale, this applied scientist role is Builds AI ●●●●: the job is building AI systems.
- The listed pay starts 10% above the typical applied scientist posting on Level.
- Tools and skills the posting cites include TensorFlow, scikit-learn and computer vision.
- Level lists 22,000+ other open roles at Amazon.
- The role was posted in the last few days.
AI in this role
Basic qualifications
- 6+ years of building machine learning models or developing algorithms for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Experience with neural deep learning methods and machine learning
- Knowledge of programming languages such as C/C++, Python, Java or Perl
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.
- Experience in building machine learning models for business application
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, NY, New York - 183,800.00 - 248,700.00 USD annually
USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually
How we rate this
Sr Applied Scientist, CreativeX at Amazon rates 88 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in applied scientist jobs at this level
Pay
- This job starts at
- $184k
- Typical applied scientist job
- $167k
This posting starts 10% above the typical applied scientist job. See applied scientist jobs
Questions you could be asked
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Walk me through how you've used TensorFlow in your day-to-day work.
- What are the limits of scikit-learn that you've run into, and how did you work around them?
- 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: Computer vision, 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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