Applied Scientist, Alexa Edge AI

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

Job summary

Amazon’s Alexa Edge AI team in Bengaluru is seeking an Applied Scientist to design, develop, and deploy cutting-edge ML models spanning CV, audio, and multimodal understanding for edge and cloud systems. You will own the ML lifecycle, drive innovation, and help shape the team culture as a founding member of the Bangalore site.

Ideal candidates hold a PhD or Master’s with 3+ years in ML/CS, plus hands-on experience in deep learning for CV and multimodal tasks.

Qualifications

• PhD or Master’s degree with 3+ years of CS/CE/ML experience.
• 1+ years of building models for business applications.
• Experience programming in Java, C++, Python.
• Experience developing and implementing deep learning algorithms, especially CV

Responsibilities

• Design, develop, and deploy ML models for CV, audio, and multimodal tasks for edge and cloud deployments.
• Own the full ML lifecycle from problem formulation to deployment at scale.
• Stay at the frontier of CV, audio ML, and multimodal learning; publish in top venues.
• Help hire, onboard, and establish technical practices as a founding Bangalore site member

Skills

Java programming

C++ programming

Python programming

Deep learning

Education

PhD or Master’s in CS/CE/ML

Tools

Distributed training

Job description

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 developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms

Preferred Qualifications

• Knowledge of standard speech and machine learning techniques
• 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.)
• Publications at top-tier ML/CV/Audio conferences
• Demonstrated ability to work in ambiguous, fast-paced environments and define technical roadmaps independently

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.

Company

ADCI - BLR 14 SEZ