Sr. Machine learning Scientist

Job description

DESCRIPTION

We are building a team of passionate people who are focused on changing the world for the better. Driving forward with Customer Obsession & Think Big we will be creating a new vertical for Amazon. We are looking for smart, passionate people who have a strong sense of ownership and strong innovation mindset. If you want your work to positively impact the lives of millions of people and you’re up for a challenge, let’s talk!

We are looking for an Machine learning Scientist who can bring bleeding edge machine learning or NLP techniques into real products solving real problems together with a highly multi-disciplinary team of scientist, engineers, strategic partners, product managers and subject domain.

PREFERRED QUALIFICATIONS

· PhD in Natural Language Processing or Information Retrieval
· Experience and/or motivation to work on modern deep learning approaches to NLP: word/paragraph embedding, representation learning, text/sentiment classification, ambiguity disambiguation
· Experience in one or more of the following areas: entity/relation extraction, normalization, text summarization, semantic search, word/paragraph/document embedding, ranking, ontology-aware IR, question answering systems
· Knowledge of or experience in building production quality and large scale deployment of applications related to natural language processing and machine learning.
· Track-record of having developed novel algorithms, e.g. publications in one or more of the following: KDD, WWW, NIPS, NAACL, ACL, SIGIR, EMNLP, ICML etc
· Experience with filesystems, server architectures, and distributed systems

Meets/exceeds Amazon’s leadership principles requirements for this role

Meets/exceeds Amazon’s functional/technical depth and complexity for this role

Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation

Desired profile

BASIC QUALIFICATIONS

· PhD in machine learning (or in a highly related area) or equivalent experience
· Solid background in statistical learning techniques for Deep Learning, HMMs, CRFs, SVMs, LDA, LSI, MRFs etc
· Fluency with at least one of the modern distributed ML frameworks such as TensorFlow, PyTorch, MxNet.
· Must have ML algorithm implementation experience as well as the ability to modify standard algorithms (e.g. change objectives, work-out the math and implement)
· Strong programming skills in at least one object oriented programming language (Java, Scala, C++, Python, etc.)
· Eager to learn new algorithms, new application areas and new tools.