We are looking for a Senior Applied Scientist to help establish and lead the technical direction of our newly formed team in Bangalore. In this role, you will drive the research and development of next-generation machine learning models spanning computer vision, audio processing, and multimodal semantic understanding. You will help define the science roadmap, tackle high‐ambiguity problems across modalities, and deliver solutions that operate at scale. This is a rare opportunity to shape the technical vision, culture, and long‐term research agenda of a greenfield site.
Key ResponsibilitiesModel Development & Technical Leadership: Architect and drive development of advanced deep learning models for CV, audio understanding, and multimodal semantic fusion – setting the technical bar and defining best practices for the team.
End-to-End Ownership: Own complex ML programs end-to-end – from identifying high‐impact problems, designing data strategies and evaluation frameworks, through experimentation, optimization, and deployment at production scale.
Research & Innovation: Define the science roadmap for your area;
drive novel research directions in multimodal learning and deliver results that advance both the product and the broader field.
Publications & Thought Leadership: Maintain an active publication record at top‐tier venues (e.G., CVPR, NeurIPS, ICASSP, ICCV, ACL) and represent the team externally in the research community.
Mentorship & Culture Building: Mentor scientists and engineers, raise the technical bar through hiring, and play a foundational role in establishing the Bangalore site's culture, processes, and scientific identity.
A Day in the LifeAn Applied Scientist with the Alexa Edge AI team will lead 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, a Sr. Applied Scientist will also drive cross‐functional collaboration with talented engineers and scientists to put algorithms and models into production.
About the TeamThe 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 6+ years of applied research experience
5+ years of building machine learning models for business application experience
Experience programming in Java, C++, Python or related language
Preferred Qualifications
5+ years of hands‐on experience building and deploying ML/DL models in computer vision, audio/speech processing, or multimodal learning
Proven track record of leading technical initiatives from conception to production impact
Deep expertise in modern neural architectures (transformers, diffusion models, foundation models)
Experience defining science roadmaps and influencing cross‐functional priorities
Familiarity with distributed training at scale, model compression, and low‐latency inference
Strong publication record at top‐tier ML/CV/Audio conferences
Track record of mentoring junior scientists and building high‐performing research teams
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