Applied Scientist II, Alexa International Tech

Amazon; Bengaluru; On-site; INR 1,500,000 - 3,000,000; Full time

Job summary

Amazon is seeking an Applied Scientist for the Alexa International team in Bengaluru to advance Large Language Models, ASR, TTS, and multimodal speech systems. You will develop novel algorithms, model techniques, and evaluation metrics for scalable, international digital assistant solutions.

You will work with a global team, leverage large-scale data, and push state-of-the-art methods while delivering high-quality results for Amazon's international customers and services.

Qualifications

• 3+ years building ML models for business applications.
• PhD or Master’s with 4+ years in CS/CE/ML or related field.

Responsibilities

• Analyze, understand, and model customer behavior based on large-scale data.
• Build online and offline evaluation metrics for multimodal personal digital assistants.
• Drive research in ASR, TTS, and Speech-to-Speech model training and fine-tuning.
• Advance multilingual speech recognition and synthesis using LLM-based architectures.
• Fine-tune/post-train LLMs using SFT, DPO, RLHF, and RLAIF.
• Collaborate with partner teams on evaluation frameworks and post-training methodologies.
• Communicate solutions clearly to partners and stakeholders.
• Contribute to the scientific community through publications and community engagement.

Skills

Java

C++

Python

ASR/TTS

LLM integration

Publications

Multimodal models

Deep learning

Education

PhD

Master's degree in CS/CE/ML

Tools

Unix/Linux

Job description

Alexa International is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technology with Large Language Models (LLMs), ASR, TTS, and Speech to Speech models, requiring strong deep learning and generative models knowledge. You will contribute to developing novel solutions and deliver high-quality results 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 novel algorithms and modeling techniques to advance the state of the art with Large Language Models (LLMs), ASR, TTS, and Speech to Speech model. Your work will directly impact our international customers in the form of products and services that make use of digital assistant technology. You will leverage Amazon's heterogeneous data sources, unique and diverse international customer nuances and large-scale computing resources to accelerate advances in text, voice, and vision domains in a multimodal setup.

A day in the life

• Analyze, understand, and model customer behavior and the customer experience based on large-scale data.
• Build novel online & offline evaluation metrics and methodologies for multimodal personal digital assistants.
• Drive research in ASR, TTS, and Speech-to-Speech (S2S) model training and fine-tuning
• Advance multilingual speech recognition and synthesis using LLM-based architectures
• Fine-tune/post-train LLMs using techniques like SFT, DPO, RLHF, and RLAIF.
• Collaborate with partner teams on evaluation frameworks and post-training methodologies.
• Communicate solutions clearly to partners and stakeholders.
• Contribute to the scientific community through publications and community engagement.

Basic Qualifications

• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience in patents or publications at top-tier peer-reviewed conferences or journals
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• Experience programming in Java, C++, Python or related language
• Deep expertise in ASR/TTS architectures, end-to-end speech models, and LLM integration with speech systems

Preferred Qualifications

• Experience using Unix/Linux
• Experience building machine learning models or developing algorithms for business application
• Deep expertise in state-of-the-art LLM architectures, training, evaluation, and post-training techniques (SFT, DPO, RLHF, RLAIF)

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