ADCI
Technology
PrincipalAppliedScientist,HardwareSiliconandSystemsGroup
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“Principal Applied Scientist, Hardware Silicon and Systems Group at ADCI. Skills: ML models, Hardware optimization, Model compression, On-device ML. Own technical architecture. Optimize ML models”
Industry & Context.
What They're Looking For.
Must Have
Masters degree in Computer Science, 8+ years of experience in machine learning, Expertise in developing deep learning models, Background in computer architecture, Hands-on experience with model compression techniques, Proficiency with deep learning frameworks
Nice to Have
PhD in Computer Science, 10+ years of experience in machine learning, Proven expertise in co-designing ML models, In-depth understanding of model compression, Experience working on resource-constrained embedded systems, Demonstrated ability to influence technical strategy, Mentor cross-functional teams
What You'll Do.
Own technical architecture
Develop novel model architectures
Establish methodologies for model compression
Create evaluation framework
Implement multimodal optimization techniques
Define technical standards
Drive research initiatives
Develop novel ML architectures
Write critical optimization code
Create proof-of-concept implementations
Influence architecture decisions
Establish standards for model optimization
How You'll Work.
Team & Collaboration
Cross-functional teams
Full Job Description
Hardware Silicon and Systems Group leads the development and optimization of on-device ML models for Amazon's hardware products, including audio, vision, and multi-modal AI features. We work at the critical intersection of ML innovation and silicon design, ensuring AI capabilities can run efficiently on resource-constrained devices. Currently, we enable production ML models across multiple device families, including Echo, Ring/Blink, and other consumer devices. Our work directly impacts Amazon's customer experiences in consumer AI device market. The solutions we develop determine which AI features can be offered on-device versus requiring cloud connectivity, ultimately shaping product capabilities and customer experience across Amazon's hardware portfolio. This is a unique opportunity to help shape the future of AI in consumer devices at unprecedented scale. You'll be at the forefront of developing industry-first model architectures and compression techniques that will power AI features across millions of Amazon devices worldwide. Your innovations will directly enable new AI features that enhance how customers interact with Amazon products every day. As Principal Applied Scientist you will blend expertise at the intersection of ML and hardware optimization for model training, build cutting-edge architectures for vision, language, and multi-modal tasks. Role requires a specialist in hardware-aware quantization, with hands-on experience in model compression techniques like pruning and distillation. You will be responsible for computer architecture, ML accelerator designs, efficient inference algorithms and low-precision arithmetic. Key job responsibilities As a Principal Applied Scientist, you will: • Own the technical architecture and optimization strategy for ML models deployed across Amazon's device ecosystem, from existing to yet-to-be-shipped products. • Develop novel model architectures optimized for our custom silicon, establishing new methodologies for model c
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