Pittsburgh

Join the Amazon AGI team to revolutionize the future of AI by developing breakthrough technologies that dramatically improve the efficiency of large language and foundation models. Work at the frontier of AI research, designing novel approaches for model compression, efficient architectures, long context extension and training optimization that will shape the next generation of AI systems.We're seeking exceptional Applied Scientists to join our team dedicated to solving one of AI's most critical challenges: making foundation models more efficient through lower latency and higher throughput. You'll work on research and new technology development while collaborating with world-class researchers and engineers.- Pioneer new approaches to foundation models- Publish and present research at top-tier conferences and journals- Work with state-of-the-art LLMs and multi-modal foundation models - Access to substantial computational resources for research- Collaborate across AGI teams to implement solutions at scaleKey job responsibilities- Research and develop novel techniques for efficient runtime inference (low latency, high throughput)- Design and evaluate efficient foundation model architectures- Create new methods for improving training efficiency- Conduct experimental studies to validate efficiency improvements- Write high-quality Python code to implement research ideas- Collaborate with team members to integrate solutions into production systems- Author technical documentation and research papers- Present findings to technical and non-technical stakeholdersA day in the lifeYour day might start with a team stand-up to discuss ongoing projects and brainstorm solutions to technical challenges. You'll spend time implementing and testing new efficiency optimization techniques in Python, analyzing performance metrics, and iterating on approaches. You'll collaborate with team members to review code and research results, participate in technical discussions about architecture designs, and engage with other AGI teams to understand their efficiency needs. You might end your day analyzing experimental results or writing up findings for a research paper. Throughout the week, you'll have opportunities to present your work to stakeholders and contribute to the team's research roadmap.Our stakeholders include other AGI teams within Amazon, and our work directly impacts the cost and performance of AI systems used across Amazon's products and services. You'll be solving complex technical challenges that make advanced AI more accessible and efficient at scale.About the teamThe Neural Efficiency Science team was founded in 2024 to develop new technologies that improve the cost-to-performance ratio of AGI foundation models. Amazon believes in customer-obsessed research and as a large number of AI applications are getting built, we see a need to invest in making the underlying foundation models serving these applications cheaper, faster and more accurate at a given price point. Our team keeps up with all of the latest research and trends in what we call "neural efficiency" and publishes our own findings at top conferences such as ICML and NeurIPS while also making our technology available in production for internal and external customers. BASIC QUALIFICATIONS- 3+ 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 programming in Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing ...

Amazon is looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers. As a Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. We are hiring in all areas of spoken language understanding: ASR, NLU, text-to-speech (TTS), and Dialog Management. Position Responsibilities: - Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. - Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. - Routinely build and deploy ML models on available data. - Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists.BASIC QUALIFICATIONS- 3+ years of building machine learning models for business application experience- PhD, or Master's degree and 6+ years of applied research experience- Experience programming in Java, C++, Python or related language- Experience with neural deep learning methods and machine learning ...

The Sensory Inference team at AGI is a group of innovative developers working on groundbreaking multi-modal inference solutions that revolutionize how AI systems perceive and interact with the world. We push the limits of inference performance to provide the best possible experience for our users across a wide range of applications and devices. We are looking for talented, passionate, and dedicated Inference Engineers to join our team and build innovative, mission-critical, high-volume production systems that will shape the future of AI. You will have an enormous opportunity to make an impact on the design, architecture, and implementation of cutting-edge technologies used every day, potentially by people you know. This role offers the exciting chance to work in a highly technical domain at the boundary between fundamental AI research and production engineering such as Quantization, Speculative Decoding, and Long Context for inference efficiency.Key job responsibilities• Develop high-performance inference software for a diverse set of neural models, typically in C/C++• Design, prototype, and evaluate new inference engines and optimization techniques• Participate in deep-dive analysis and profiling of production code• Optimize inference performance across various platforms (on-device, cloud-based CPU, GPU, proprietary ASICs)• Collaborate closely with research scientists to bring next-generation neural models to life• Partner with internal and external hardware teams to maximize platform utilization• Work in an Agile environment to deliver high-quality software• Hold a high bar for technical excellence within the team and across the organizationBASIC QUALIFICATIONS- 3+ years of non-internship professional software development experience- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience- Experience programming with at least one software programming language- Bachelor's degree in Computer Science, Computer Engineering, or related field- Strong C/C++ programming skills- Solid understanding of deep learning architectures (CNNs, RNNs, Transformers, etc.) ...