Amazon Web Services (AWS)
Senior Machine Learning Engineer, Neuro-Symbolic AI Labs
Boston, Massachusetts · Senior
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
$18,060 more — $186,160 — moves this role to Level IV and 4 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $186,160 would place this position at wage Level IV. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Developers" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · Boston-Cambridge-Newton, MA-NH. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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About the role
- We work closely with academia.
Responsibilities
- Define and implement new neuro-symbolic applications that employ scalable and efficient approaches to solve complex problems.
- Deliver high-quality scientific artifacts.
- Our team includes an Amazon Scholar in mathematics, and we maintain active research collaborations with faculty at leading CS departments (MIT, CMU).
Requirements
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- Work in an agile, startup-like development environment, where you are always working on the most important stuff.
Nice to have
- Bachelor's degree in computer science or equivalent
- Company - Amazon Development Center U.S., Inc.
- Job ID: A10503587
Compensation
- $168k-$227k
This listing is sourced directly from Amazon Web Services (AWS)'s careers page and normalized into a canonical job model.