ADCI
Technology
AppliedScienceManager,AlexaEdgeAI
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“Applied Science Manager, Alexa Edge AI at ADCI. Skills: Edge AI, Computer vision, Acoustic modeling, Multimodal understanding. Establish and grow applied science team. Define team's charter”
What You'll Achieve.
Deliver best in class models; Deliver resource efficient models; Power hundreds of millions of devices; Deliver experiences that feel magical; Ship science that touches millions of lives
Industry & Context.
Tackling hard constraints
What They're Looking For.
Must Have
Master's degree and 8+ years of applied research experience, 3+ years of building machine learning models for business application experience, Experience managing and deploying ML products, Deep expertise in computer vision, Deep expertise in acoustic/speech modeling, Deep expertise in multimodal learning
Nice to Have
PhD, Experience in building and developing a high performance team, Experience with multimodal LLM for visual or speech understanding, Experience with on-device/edge ML deployment and optimization, Publication track record at top-tier ML/CV/Speech conferences
What You'll Do.
Establish and grow applied science team
Define team's charter
Define team's culture
Define technical roadmap
Foster scientific rigor
Foster rapid experimentation
Foster customer obsession
Foster operational excellence
Drive R&D of privacy preserving edge solutions
Optimize Visual recognition
Optimize Acoustic Modeling
Optimize edge deployment
Define strategies for optimizing latency
Define strategies for optimizing privacy
Define strategies for optimizing accuracy
Define strategies for optimizing cost
Collaborate with hardware teams
Collaborate with silicon teams
Co-design AI accelerators
Co-design model architectures
Own end-to-end lifecycle
Establish robust benchmarking
Establish A/B testing
Establish metrics frameworks
Measure real-world impact
Partner with engineering teams
Partner with product teams
Partner with UX teams
Translate scientific breakthroughs
Shape science roadmap
Shape technology roadmap
Represent team in science reviews
Represent team in patent filings
Represent team in publications
Build cross-site collaboration
How You'll Work.
Team & Collaboration
Cross-site collaboration; Hardware teams; Silicon teams; Engineering teams; Product teams; UX teams
Communication Scope
Org-wide science reviews; Patent filings; Publications
Process & Methodology
Roadmap planning
Full Job Description
Are you ready to build something extraordinary from the ground up? We're looking for a seasoned Applied Science Manager to establish and lead a brand-new team in Bangalore, India, within Alexa Edge AI. This is a rare greenfield opportunity to shape the future of ambient intelligence by pioneering breakthroughs in computer vision, acoustic modeling, and multimodal semantic understanding that will power hundreds of millions of Alexa-enabled devices worldwide. As an Applied Science Manager, you will architect and scale a world-class applied science team that pushes the boundaries of what's possible at the intersection of edge and cloud AI. From enabling seamless Visual ID that recognizes who's in the room, to crafting ultra-low-latency wake word detection that works flawlessly in noisy environments, to building multimodal models that build deep semantic understanding — your work will directly define how Alexa perceives, understands, and interacts with the physical world. You'll operate at the frontier of on-device ML, tackling hard constraints in compute, memory, and power while delivering experiences that feel magical to customers. If you thrive on ambiguity, love building high-performing teams from scratch, and want to ship science that touches millions of lives daily — this is your moment. Key job responsibilities Establish and grow a high-caliber applied science team from the ground up at our new Bangalore site, defining the team's charter, culture, hiring bar, and technical roadmap Recruit, mentor, and develop top-tier scientists and engineers across computer vision, speech/acoustics, and multimodal ML disciplines Foster a culture of scientific rigor, rapid experimentation, customer obsession, and operational excellence Drive R&D of privacy preserving edge solutions like Visual recognition and Acoustic Modeling (Wake Word & Audio Intelligence) optimized for edge deployment on resource-constrained hardware (custom silicon, DSPs, NPUs). Define and execute strategies
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