Applied Scientist II, Alexa Devices, GENIE Science

Amazon; Toronto; On-site; CAD 100,000 - 150,000; Full time

Job summary

A leading technology company in Toronto is seeking an Applied Scientist to develop scalable solutions utilizing machine learning and NLP technologies. You will work with advanced systems aimed at enhancing customer experiences through proactive and personalized interactions. The best candidates will have a strong machine learning background, programming skills in languages like Java and Python, and experience in delivering impactful business applications.

Qualifications

• 3+ years of building machine learning models for business applications.
• Experience in programming languages including Java, C++, Python.
• Familiarity with deep learning methodologies.

Responsibilities

• Collaborate with scientists and engineers to develop algorithms.
• Enable timely and relevant recommendations and conversations.
• Leverage data sources and computing resources for innovations.

Skills

Machine learning

Natural Language Processing

Programming in Java

Programming in Python

Recommender Systems

Education

PhD in a relevant field

Master's degree and 3+ years of experience

Tools

Java

C++

Python

Job description

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 an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.