Applied Scientist II, SSG Science
Teknik, data och digitalt · Data, AI och analys · Maskininlärning · Datavetenskap · Mjukvaruutveckling
I korthet
Amazon Devices is seeking an Applied Scientist II to develop and optimize next-generation edge models, specifically Gen AI, for consumer products. This role involves understanding and improving the Neural Edge Engine, collaborating with cross-functional teams, and publishing research. A PhD or Master's degree with relevant experience in ML, CS, or CE is required, along with strong programming and mathematical skills.
Ansvarsområden
- Quantize, prune, distill, and finetune Gen AI models for edge platforms.
- Understand Amazon's Neural Edge Engine to invent optimization techniques.
- Analyze deep learning workloads and map them to Amazon's Neural Edge Engine.
- Utilize principles of Information Theory, Scientific Computing, Deep Learning Theory, and Non Equilibrium Thermodynamics.
- Train custom Gen AI models that achieve state-of-the-art performance.
- Collaborate with compiler engineers, Applied Scientists, Hardware Architects, and product teams.
- Publish in open source and present at ML conferences like NeurIPS, ICLR, MLSys.
Krav
- 2+ years of building models for business application experience.
- PhD or Master's degree and 4+ years of CS, CE, ML, or related field experience.
- Experience in patents or publications at top-tier peer-reviewed conferences or journals.
- Experience programming in Java, C++, Python, or a related language.
- Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high-performance computing.
- Strong foundation in relevant mathematical concepts (linear algebra, calculus, etc.).
Önskade kvalifikationer
- Experience in professional software development.
- Prior experience in productionizing ML models and managing their full lifecycle from development to deployment.
Förmåner
- Inclusive culture that empowers employees.
- Opportunity to work on state-of-the-art techniques and revolutionary architecture.
- Develop the next generation of edge models.
#AI#Machine Learning#Deep Learning#Edge Computing#Hardware#Consumer Products