Applied Scientist II, Alexa AI, GENIE Science

Amazon; Toronto; On-site; CAD 80,000 - 130,000; Full time

Job summary

An innovative organization within a leading tech company is seeking an Applied Scientist specialized in Natural Language Processing and Recommender Systems. This exciting role involves developing advanced algorithms that enhance customer interactions through personalized experiences. You will work with cutting-edge machine learning and deep learning technologies, contributing to impactful products and services. If you are passionate about solving complex problems and enjoy a dynamic work environment, this position offers the opportunity to make a significant difference in the lives of users through technology.

Qualifications

• PhD or Master's with 3+ years of experience in machine learning for business applications.
• Experience programming in Java, C++, or Python.

Responsibilities

• Collaborate to develop novel algorithms for recommendations and conversations.
• Leverage data sources and computing resources for advancements in machine learning.

Skills

Machine Learning

Natural Language Processing (NLP)

Recommender Systems

Information Retrieval

Programming (Java, C++, Python)

Deep Learning

Software Development

Communication Skills

Education

PhD in relevant field

Master's degree

Job description

We are a part of Amazon Alexa Devices organization with the mission “delight customers through contextual and personalized proactive experiences that keep customers informed, engaged, and productive without cognitive burden”.
We are developing an advanced system using Large Language Model (LLM) technologies to deliver engaging, intuitive, and adaptive content recommendations across all Amazon surfaces. We aim to facilitate seamless reasoning and customer experiences, surpassing the capabilities of previous machine learning models. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware speech assistant. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions.

Key job responsibilities

As an Applied Scientist on the team, you will collaborate with other applied scientists and engineers to develop novel algorithms to enable timely, relevant and delightful recommendations and conversations. Your work will directly impact our customers in the form of products and services that make use of various machine learning, deep learning and language model technologies. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in the state of art.

BASIC QUALIFICATIONS

- PhD, or Master's degree and 3+ years of building machine learning models for business application experience
- 3+ years of building models for business application experience
- Experience programming in Java, C++, Python or related language

PREFERRED QUALIFICATIONS

- PhD in Electrical Engineering, Computer Sciences, or Mathematics with specialties in natural language processing, recommendation system, information retrieval
- 2+ years experience in building machine learning or deep learning models for large scale customer facing product or features.
- Publications at peer-reviewed NLP/ML conferences (e.g. ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI)
- Solid software development experience
- Good written and verbal communication skills

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, disability, age, or other legally protected status.