Applied Scientist, Alexa Connections

Job summary

You will research, develop, and deploy language intelligence using large language models to power communication features like summarization and smart replies. You will collaborate with engineering and product teams to scale these models while ensuring quality, latency, and customer privacy.

Job details

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 [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

What you’ll do

You will research, develop, and deploy language intelligence using large language models to power communication features like summarization and smart replies. You will collaborate with engineering and product teams to scale these models while ensuring quality, latency, and customer privacy.

Requirements

Candidates must have a PhD or a Master's degree with at least 4 years of experience in machine learning or algorithm development. Proficiency in Java, C++, or Python and proven experience deploying NLP models in production environments are required.

Benefits

• Health insurance • Medical insurance • Dental insurance • Vision insurance • Prescription insurance • Basic life insurance • AD&D insurance • Registered Retirement Savings Plan • Deferred Profit Sharing Plan • Paid time off • Restricted stock units

Listed skills

• Machine learning · Preferred
• Java · Preferred
• C++ · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine learning
• Natural language processing
• Large language models
• Java
• C++
• Python
• Named entity recognition
• Entity linking
• Intent detection
• Retrieval-augmented generation
• Conversational AI
• Dialogue systems
• Coreference resolution
• Summarization
• Instruction-tuning
• In-context learning
• Large Language Modeling
• Time Off Management
• Retrieval Augmented Generation
• Research
• Algorithms
• Business Software
• C++ (Programming Language)
• Communication
• Computer Science
• Python (Programming Language)
• Language Experience Approach
• Machine Learning
• Machine Translation
• Medical Prescription
• Named Entity Recognition
• Natural Language Processing (NLP)
• Restricted Stock
• Transcribing

Job areas

• Technology
• Software
• Science & Research
• Data & Analytics
• Engineering
• Applied Scientist
• Research Scientist
• Physical and Engineering Science Technicians Not Elsewhere Classified
• Medical Scientists, Except Epidemiologists