Sr. Applied Scientist

Key Skills

Java Programming, Python Programming, C++, SQL, Azure, Machine learning techniques, Keras software library, Natural Language Processing (NLP), PyTorch, TensorFlow, Docker, Kubernetes-K8s, Google Cloud Platform (GCP), MxNet, SPARK Programming, AWS Sagemaker, Caffe, C# Programming, Large scale data processing

Job Description

The Amazon Product Catalog group is hiring a Senior Applied Scientist to help us build the most authoritative product knowledge in existence. Our charter is to capture every relevant fact and relationship for any product on the planet. You will have an enormous opportunity to make a large impact on the design, architecture, and implementation of cutting edge products used every day, by people you know.

As a Senior Applied Scientist, you will be responsible for designing, developing, and deploying large-scale data mining solutions and distributed machine learning systems that ultimately make shopping on Amazon delightful and functional. Because the product catalog is the heart of our retail business, your work will directly change how Amazon customers search, find, compare, and buy everything from televisions to groceries. Our catalog contains hundreds of billions of facts, a scale which demands automated, state-of-the-art techniques to identify defects, abuse, incorrect data, and find new relationships between products, facts, and entities.

Our domain blurs the boundaries between knowledge graphs, ontologies, entity recognition, image classification, machine translation, entity recognition, and semantic fact extraction. This requires a fast, collaborative environment We not only leverage best-in-class models, but also improve them. You will have the support of a well-established team with a long-term charter, science-smart engineers, language experts, and the latest AWS products and compute resources. You will collaborate closely with teams of software engineers, applied machine learning scientists, product managers, user interface designers, and others in order to influence our business and technical strategy, and play a key role in defining the team’s roadmap.

A successful candidate will have an established background in machine learning science, large scale software systems, a strong technical ability, great communication skills, and a motivation to solve new, ambiguous problems.

Unique Opportunities

• Global impact on hundreds of millions of Amazon customers
• Opportunities to publish both internally and externally
• Close-knit partnership with science-smart developers – your improvements can roll out in days, not months, because engineers understand your work
• Access to Amazon-scale datasets, spanning hundreds of billions of facts
• Support from over 100 dedicated language experts and SMEs to label, validate, and test your hypothesis
• Challenging, cutting-edge science problems that cross multiple domains (such as textual, semantic and image-aware Transformer models )

Key Responsibilities

• Develop production-ready machine learning solutions to improve Amazon Product Catalog
• Collaborate with and influence scientists and engineers in multiple teams
• Refine existing techniques, optimizing accuracy, throughput, and global impact
• Publish results internally and externally

BASIC QUALIFICATIONS

• PhD degree with 4+ years of applied research experience or a Master's degree and 6+ years of experience of applied research experience
• 3+ years of experience in building machine learning models for business application
• Experience programming in Java, C++, Python or related language

• PhD degree with 4 years of applied research experience, or a Masters degree and 6+ years of experience of applied research experience
• At least 5+ years of hands-on, practical experience building machine learning models for business applications
• At least 2+ years of hands-on, practical experience with Python, Java, C#, C++ or other similar languages
• Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis
• Strength distilling problem definitions, models, and constraints from complex business problems and requirements
• Strong Ability to convey complex results to non-science stakeholders

PREFERRED QUALIFICATIONS

• Ph.D. in Computer Science, Machine Learning, Operational Research, Artificial Intelligence, or a related technical field
• 7+ years of practical experience applying machine learning to solve complex problems in an applied environment
• Experience in one or more of the following: natural language processing (NLP), image recognition, deep learning, recommendation systems, information retrieval, machine translation, knowledge graphs, or speech processing
• Proficiency with one or more of the following: Tensorflow, Pytorch, Keras, MXNet, CAFFE, Spark, Cloud-based model and/or container deployment technologies (AWS Sagemaker, Fargate, ECS, GCP, Azure, Kubernetes, Docker, etc)
• Proficiency in end-to-end model development, validation, and model deployment for large-scale applications
• Proven track record in technically leading and mentoring scientists
• Publication history, including top journals and conferences