Do you want to join an innovative team of engineers and scientists who use terabytes of data and create state-of-the-art algorithms to push the boundaries of AI?
We are building the foundational behavioral model for Amazon Stores using LLM and Large Model training techniques that fuses general world knowledge with Amazon e-commerce domain knowledge.
We are searching for engineers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry.
So, if you're passionate about pushing the limits of AI, thrive in a fast-paced and innovative environment, and are ready to make a lasting impact on the world, this is your chance! Join us on this revolutionizing adventure!
Key job responsibilities
In this role you will leverage your engineering background and expertise in ML to lead developing foundational behavioral model for Amazon Stores using LLM and Large Model training techniques.
On a day-to-day basis, you will :
- Lead the design and implementation of a stable and efficient training infrastructure that scales to a large model size and hardware such as GPU.
- Collaborate with other talented applied scientists and engineers to develop an improved training infrastructure that accelerates innovation.
- Quickly learn cutting-edge technologies and algorithms in the field of Generative AI.
BASIC QUALIFICATIONS
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- Experience in developing machine learning pipelines, developing large language model or natural language understanding models.
PREFERRED QUALIFICATIONS
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Master or PhD in Computer Sciences, Electrical Engineering, or Mathematics with specialization in machine learning, deep learning, or natural language processing
- Experience with CUDA
- Experience with Pytorch or Tensorflow
- Experience with distributed training
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