Applied Scientist, Alexa International Tech

Amazon Science; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Amazon Science is seeking an Applied Scientist to help advance Alexa's multilingual capabilities using LLMs, ASR, TTS, and Speech-to-Speech systems. You will build, evaluate, and deploy models across languages and regions, leveraging large-scale data and computing resources.

The role emphasizes research and practical impact, with collaboration across teams to deliver production-ready scientific solutions for Alexa's international products and services.

Qualifications

• Proficient in modern ML/NLP concepts and model evaluation.
• Experience with large-scale ML systems and multilingual models.

Responsibilities

• Analyze data and develop algorithms for multilingual speech/NLP tasks.
• Implement and evaluate LLM-based models and ASR/TTS/S2S components.
• Collaborate with cross-functional teams to advance Alexa's multilingual capabilities.
• Publish research findings and contribute to practical production systems.

Job description

Description

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

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