As a Machine Learning Engineer, you will work closely with science teams to bring research to production. This is a role that combines engineering knowledge (around machine learning, natural language processing, computer vision), technical strength, and product focus. It will be your job to implement novel ML systems, product integrations, and performance optimizations. You will guide the direction of the AutoGluon framework via collaboration with the open-source, academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. You will have the opportunity to publish in scientific conferences and journals, create white papers, write blogs, and have high visibility in the industry.
About the team
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
We are open to hiring candidates to work out of one of the following locations:
Bellevue, WA, USA | Santa Clara, CA, USA
BASIC QUALIFICATIONS
– 5+ years of non-internship professional software development experience
– 3+ 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
– Experience as a mentor, tech lead or leading an engineering team
PREFERRED QUALIFICATIONS
– 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
– Master’s degree in computer science or equivalent
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 $115,000/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. Applicants should apply via our internal or external career site.
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