Applied Scientist, Alexa Connections

Amazon is hiring an Applied Scientist, Alexa Connections in Vancouver, Canada. It pays CAD 149k-CAD 249k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this applied scientist role is Builds AI ●●●●: the job is building AI systems.
The posting mentions Python, Java and C among its tools and skills.
Level classes it as a senior role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Researches and develops LLM-powered language intelligence and agentic communication features for Alexa.

PythonJavaCLLMsRAG

ragnlpspeechmachine-learningapplied-sciencemodel-fine-tuningretrieval-augmented-generation

Alexa Connections is on a mission to become the world's most trusted communication agent, spanning calls, text, email, and the ever-expanding surfaces where people connect. We're building intelligence that keeps customers connected effortlessly while putting their trust and privacy first. As an Applied Scientist, you'll help build the smartest communications agent for people, an agent that understands intent, context, and relationships, and that acts on a customer's behalf to make every interaction feel effortless and genuinely helpful

Key job responsibilities
You'll research, develop, and deploy the language intelligence that powers how people communicate, using and adapting large language models to understand intent, context, and the entities that matter in a conversation, the people, contacts, events, dates, and topics that tell the agent who and what a message is about. In practice, that means reframing classic NLP and named entity recognition as LLM-native tasks through instruction-tuning, in-context learning, and structured generation, and building agentic capabilities that reason over multi-turn conversations and act on them, from summarization and smart replies to coreference and context resolution grounded in a customer's relationships and history. You'll fine-tune, align, and optimize foundation models for the messiness of real communication data, informal text, code-switching, misspellings, transcribed speech, and multilingual content, and ground their outputs in customer context using retrieval-augmented generation and personalization so responses stay relevant and reliable. Throughout, you'll take models from research to production at scale, partnering with engineering and product teams to ship LLM-powered features used by millions every day, and define the evaluation frameworks that measure quality, faithfulness, latency, and customer impact while keeping trust and privacy first.

Basic qualifications

- PhD, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience
- 2+ years of programming in Java, C++, Python or related language experience
- Experience building and deploying NLP models in production, such as named entity recognition, entity linking, intent detection, or language understanding

Preferred qualifications

- PhD in computer science, machine learning, engineering, or related fields
- Knowledge of standard speech and machine learning techniques
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
- Experience applying large language models to NLP tasks, including instruction-tuning, in-context learning, or retrieval-augmented generation (RAG)
- Experience with conversational AI, dialogue systems, or communication/messaging applications
- Experience with multilingual NLP, coreference resolution, summarization, or working with noisy real-world text (transcribed speech, informal messaging

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.

The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.

CAN, BC, Vancouver - 149,300.00 - 249,300.00 CAD annually
CAN, ON, Toronto - 149,300.00 - 249,300.00 CAD annually

How we rate this

Applied Scientist, Alexa Connections at Amazon rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Applied Scientist, Alexa Connections is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is CAD 149k-CAD 249k a year.
The role is based in CA, BC, Vancouver.
The job was posted on September 23, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGNLPSpeechMachine learningApplied ScienceModel Fine TuningRetrieval Augmented GenerationPython

Also common in applied scientist jobs at this level

Deep learning Generative AI Reinforcement learning TensorFlow Spark AWS

Pay

Typical applied scientist job: $167k

Use the typical applied scientist figure as a reference when pay comes up. See applied scientist jobs

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
What NLP problem have you worked on, and how did you measure whether it actually worked?
What have you built with speech recognition or text-to-speech, and where did it break?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where applied science was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: RAG, NLP, Speech, Machine learning, and Applied Science. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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