Amazon

Returning Candidate?

Machine Learning Software Dev Engineer

Machine Learning Software Dev Engineer

Job ID 
530258
Company/Location (search) 
US-CA-Palo Alto
Posted Date 
10/6/2017
Company 
Amazon Corporate LLC
Recruiting Team 
..

Job Description

Have you ever wanted to work on state of the art computer vision, natural language processing and applied machine learning that will make a lasting impact on society?

We are looking for brilliant Machine Learning Software Dev Engineers who have the passion to tackle tough problems by bringing cutting edge deep learning technologies to consumer IoT products at Amazon!

As a Machine Learning Software Dev Engineer on the Amazon AI Team, you will design and develop fast, efficient, and highly scalable deep learning algorithms that are applied to challenging every-day use case problems. You'll work with senior scientists and engineers within Amazon AI and develop high quality software that is robust and reliable.

Software Engineers at Amazon do so much more than just software development. We'll be looking at you to help:
· Decide what features to build.
· Drive software engineering best practice.
· Design distributed and scalable systems.
· Test and document the software you develop.


Basic Qualifications

· BS, MS in Computer Science, Applied Math or related Engineering fields with 5+ years of relevant work experience.
· Computer Science fundamentals in object-oriented design, data structures, high-performance computing (HPC).
· Computer Science fundamentals in algorithm design, complexity analysis, problem solving and diagnosis.
· Proficiency in, at least, one modern programming language such as Java, C++ and Python.
· Can translate user inputs to software requirements and design specifications and effectively communicate with team members.

Preferred Qualifications

Preferred Qualifications
· Ph.D. with 3 years of relevant experience.
· Experience with machine learning, deep learning, data mining, and/or statistical analysis tools.
· Experience taking projects from scoping requirements through V1 launch and V2 iterations.
· Knowledge of professional software engineering practices and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
· Experience with highly distributed systems.
· Experience designing high performance software and algorithms for resource constrained IoT and mobile environments.
· Proficiency training large scale models in, at least, one modern deep learning engine such as MXNet, Tensorflow, Caffe/Caffe2, Keras, PyTorch/Torch and Theano.
· Experience in GPU, FPGA, DSP acceleration and performance tuning.
· Experience in production-scale software development with ML/AI, computer vision and smart IoT device.