Amazon Devices is building products to enable new forms of ambient computing, and we are looking for skilled and passionate applied scientists to join our world-class, growing team. As an Applied Scientist, you will be conceiving, designing, and bringing to market computer vision techniques for a new-to-world smart-home product. In this role, you will work daily on challenging problems from the perspective of both a research and production engineer. You will be responsible for developing techni... more details
DESCRIPTION
Amazon Devices is building products to enable new forms of ambient computing, and we are looking for skilled and passionate applied scientists to join our world-class, growing team.
As an Applied Scientist, you will be conceiving, designing, and bringing to market computer vision techniques for a new-to-world smart-home product. In this role, you will work daily on challenging problems from the perspective of both a research and production engineer. You will be responsible for developing techniques from invention to validation, and working cross-functionally to ship your algorithms into production. Broad knowledge of modern computer vision techniques, and how to apply them in practice, is required. You will need to develop new algorithms, drawing from state of the art methods, and be able to adapt them in order to work for new use cases in customers homes.
This is a greenfield development effort, where you will need to define models, drive best engineering practices, and produce clean, re-usable code. You must be prepared to deal with ambiguity and be ready to learn as you go. You will have the opportunity to influence product decisions and direction that will impact millions of customers.
Key job responsibilities - Develop GenAI applications - Train and evaluate LLM models across different platforms - Optimize various machine learning models including pruning and distillation, in addition to edge / cloud deployment - Research, develop, implement and evaluate novel CV algorithms - Work closely with software engineering teams to build scalable, real-time implementations - Collaborate with team members on developing systems from prototyping to production level
About the team This role is on a cross-functional team with a startup mentality. Were moving fast and have ample growth and development opportunities.
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux - Experience in professional software development
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/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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