Applied Scientist, Alexa Edge AI

Amazon; India; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Amazon in Bangalore's Alexa Edge AI team is looking for an Applied Scientist to design, develop, and deploy state-of-the-art ML models spanning computer vision, audio processing, and multimodal semantic understanding for edge and cloud deployment.

You will own the full ML lifecycle, from problem formulation and data strategy to experimentation, evaluation, deployment at scale, and mentoring as a founding member of the Bangalore site.

Qualifications

• PhD or Master's degree with 3+ years CS/CE/ML experience.
• 1+ years building models for business applications.
• Experience programming in Java, C++, Python.
• Experience in speech recognition, machine translation and NLP systems.

Responsibilities

• Design and build deep learning models for CV, audio, and multimodal fusion.
• Own the full ML lifecycle from problem definition to deployment at scale.
• Stay at the frontier of CV/audio ML and contribute to publications or patents.
• As a founding member, help hire, onboard, and define technical practices.

Skills

Java

C++

Python

Education

PhD

Master's degree

Job description

The Alexa Edge AI team is seeking a talented and motivated Applied Scientist to join our newly established team in Bangalore. In this role, you will design, develop, and deploy state-of-the-art machine learning models spanning computer vision (CV), audio (including speech) processing, and multimodal semantic understanding for both edge and cloud deployment. You will work at the intersection of multiple modalities to build systems that can perceive, interpret, and reason about the world — pushing the boundaries of what's possible in unified multimodal intelligence. This is a unique opportunity to be a founding member of a brand-new site, shaping the team culture, technical direction, and research agenda from the ground up.

Key job responsibilities

• Model Development: Design and build deep learning models for computer vision, audio understanding, and multimodal semantic fusion — including architectures that enable joint reasoning across visual, auditory, and textual modalities.
• End-to-End Ownership: Own the full ML lifecycle — from problem formulation, data strategy, and annotation design through experimentation, evaluation frameworks, model optimization, and deployment at scale.
• Research & Innovation: Stay at the frontier of CV, audio ML, and multimodal learning; identify and apply SOTA techniques and contribute to the scientific community through papers at top-tier venues (CVPR, NeurIPS, ICASSP, ICCV, ACL).
• Mentorship & Culture Building: As a founding member of the Bangalore site, help hire, onboard, and establish the technical practices that define the team's culture.

A day in the life

An Applied Scientist with the Alexa Edge AI team will support science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into production.

About the team

The Alexa Edge AI team has a mission to deliver best in class, resource efficient multimodal AI models in support of various perception (vision, audio and speech) and semantic understanding based applications for devices like Echo Show series within Amazon.

Basic Qualifications

• - PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience
• - 1+ years of building models for business application experience
• - Experience programming in Java, C++, Python or related language
• - Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)

Preferred Qualifications

• - Knowledge of standard speech and machine learning techniques
• - Experience in patents or publications at top-tier peer-reviewed conferences or journals
• - PhD or work experience in a relevant field (CV, Audio, multimodal language models) Experience with distributed training, model compression, and inference optimization (e.g. pruning, quantization, distillation, etc.)
• - Demonstrated ability to work in ambiguous, fast-paced environments and define technical roadmaps independently

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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.