Описание
Amazon AI is looking for a machine learning engineer to be part of inference optimization team working on optimizing large language OSS models like Qwen, Gemma, gptoss, improving inference performance by development on inference stacks like vLLM, SGLAng, performance tuning of GenAI inference on Amazon Sagemaker, Bedrock and Hyperpod. Work includes implementation of inference optimization techniques like Speculative decoding, Disaggregated Inference and CUDA kernel tuning.<br/><br/>As part of the team, you will own price-performance of amazon LLM inference on Sagemaker, Hyperpod and Bedrock. You will be working in a fast-paced, cross-disciplinary team of engineers and researchers who are leaders in the field.
You will take on challenging problems, distill real requirements, and then deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you will deliver these to production in customer facing products.<br/><br/>Inclusive Team Culture<br/>Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion.
We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.<br/><br/>Work/Life
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