As an SDE on our team, you will leverage your deep technical expertise to build reliable, scalable, and highly performant AI systems for generating, appraising, and processing data. You will also collaborate closely with Applied Scientists on modeling experiments and prototypes.
We operate at Amazon's large scale with the energy of a nimble start-up. If you have a learner's mindset, enjoy solving challenging problems, and value an inclusive team culture, you will thrive in this role, and we hope to hear from you.
Key job responsibilities
The ideal candidate for this role has a demonstrable track record of delivering successfully in a hyper-growth environment by leveraging their deep technical expertise and adapting deftly to rapidly-evolving priorities.
Responsibilities:
- Develop and maintain key components for data generation, preparation, and appraisal.
- Manage project prioritization, deliverables, and timelines.
- Illuminate trade-offs, educate the team on best practices, and influence technical strategy.
- Collaborate closely with Applied Scientists to investigate and plan experiments, prototype new technology, and evaluate technical feasibility.
- Communicate effectively with both technical and business partners.
- Operate in a dynamic environment to deliver high quality software against competitive schedules with rapidly-evolving priorities.
About the team
We're a group of passionate engineers and scientists dedicated to pushing the boundaries of innovation in the space of data generation, preparation, and appraisal.
BASIC QUALIFICATIONS
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
- Fundamental knowledge of Machine Learning algorithms and techniques
PREFERRED QUALIFICATIONS
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- Experience developing Production workflows for machine learning model training or inferencing
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.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/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.