Principal Applied Scientist EC2 Instance Placement At Amazon

DESCRIPTION

EC2 Instance Placement combines an opportunity to work on deeply challenging problems in mathematical optimization with high leverage for positive impact for AWS customers. You will have an opportunity to define a long-term science vision for our organization, translating that direction into specific plans for scientists, as well as engineering and product teams. This role is unique in how Placement widely connects to other parts of the of the AWS business – from CPU/networking throughput to data center engineering – and rewards the curious.

As a Principal Applied Scientist, you will:
· Own and drive strategic initiatives across EC2 Instance Placement
· Act as a thought leader and forward thinker, anticipating obstacles to success and helping avoid common failure modes
· Research, build, and deploy innovative combinatorial optimization and machine learning solutions, working across technical disciplines
· Partner with science, engineering, and product leaders across the business to identify and deliver innovative solutions, identify new opportunities, define the vision, and execute to continually delight customers
· Mentor scientists and support hiring science talent

BASIC QUALIFICATIONS

· Ph.D. in Operations Research, Statistics, Applied Mathematics, Computer Science or related field, or equivalent experience
· 10+ years of experience in applied science and software development
· Experience with combinatorial optimization, machine learning, or deep learning in production systems
· Proficiency in at least one modern programming language such as Python or Java
· Ability to take a complex problem from scoping requirements through actual launch of the project
· Excellent written and oral communication skills
· Proven track record leading, mentoring, and growing teams of scientists

PREFERRED QUALIFICATIONS

One or more of the following help you stand out:
· Significant peer reviewed scientific contributions in premier journals and conferences
· Experience with reinforcement learning delivering at scale customer results
· Experience with constraint programming, mathematical optimization, or mixed-integer linear programming and related tools and ecosystem
· Expertise on a broad set of ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian Non-Parametric methods
· Solid track record of thought leadership and contributions that have advanced the field

Amazon is an equal opportunities employer, and we value your passion to discover, invent, simplify and build. We welcome applications from all members of society irrespective of age, sex, disability, sexual orientation, race, religion or belief. Amazon is strongly committed to diversity within its community and especially welcomes applications from South African citizens who are members of designated groups who may contribute to Employment Equity within the workplace and the further diversification of ideas. In this regard, the relevant laws and principles associated with Employment Equity will be considered when appointing potential candidates. We are required by law to verify your ability to work lawfully in South Africa. Amazon requires that you submit a copy of either your identity document or your passport and any applicable work permit if you are a foreign national, along with an updated curriculum vitae.