AmazonPosted 1mo ago

Applied Scientist, Alexa International Tech

Applied Scientist, Alexa International Tech at Amazon scores 100 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

IN, KA, Bengalurumidfull-time

AI in this role

fine-tuningai-evaluationnlpspeech

Alexa International is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and ASR, TTS, & Speech to Speech models, requiring foundational deep learning and generative models knowledge. Applied scientists will contribute to cross-team scientific efforts, collaborate with partner teams, and deliver solutions that impact Alexa's international products and services.

Key job responsibilities
As an Applied Scientist with the Alexa International team, you will work with talented peers to develop and implement algorithms and modeling techniques to advance the state of the art with LLMs, particularly contributing to scientific research and applied AI for multi-lingual applications — a challenging area for the industry globally. Your work will directly impact our global customers in the form of products and services that support Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in text, speech, and vision domains. The ideal candidate possesses a foundational understanding of machine learning, speech and/or natural language processing, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in a fast-paced environment, like to tackle complex challenges, and are eager to deliver impactful solutions while iterating based on user feedback.

A day in the life
* Analyze, understand, and model customer behavior and the customer experience based on large-scale data.
* Build and support online & offline evaluation metrics and methodologies for multimodal personal digital assistants.
* Work on ASR, TTS, and Speech-to-Speech (S2S) model training and fine-tuning
* Fine-tune/post-train LLMs using techniques like SFT, DPO, Reinforcement Learning (RLHF and RLAIF) for supporting model performance specific to a customer's location and language.
* Experiment and help set up experimentation frameworks for agile model and data analysis or A/B testing.
* Contribute to research efforts that drive innovation forward.
* Collaborate with cross-team scientists and engineers on LLM evaluation frameworks, post-training methodologies, and best practices for international speech and language systems.
* Contribute to end-to-end delivery of scientific solutions from research to production, including reusable science components and services.
* Communicate solutions clearly to peers, partners, and stakeholders.
* Actively participate in the broader internal and external scientific community through publications and community engagement.

Basic qualifications

- Experience programming in Java, C++, Python or related language
- Master's degree in CS, CE, ML, or related field; or Bachelor's degree with 2+ years of relevant research or industry experience
- Foundational knowledge of state-of-the-art LLM architectures, training, evaluation, and post-training techniques (SFT, DPO, RLHF, RLAIF)
- Knowledge of standard speech and machine learning techniques

Preferred qualifications

- Have publications at top-tier peer-reviewed conferences or journals
- Experience in building speech recognition, machine translation and natural language processing systems
- Experience in professional software development

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.

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A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Fine TuningAI EvaluationNlpSpeech

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
How do you decide that one model's output is better than another's for a given task?
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?
How would you decide a model or AI system is ready to ship?

Adapt your resume

List these exact terms on your resume: Fine Tuning, AI Evaluation, Nlp, and Speech. 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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