Applied Scientist, Shanghai AI Lab Full-time

The AWS Shanghai AI Lab is looking for a passionate, talented, and inventive staff member in all AI domains with a strong machine learning background as an Applied Scientist.

Founded in 2018, the Shanghai Lab has been an innovation center for long-term research projects across domains such as machine learning, computer vision, natural language processing, generative AI, and open-source AI systems. These incubated projects power products across various AWS services.

As part of the lab, you will take a leadership role and join a vibrant team with diverse expertise in both machine learning and application domains. You will work on state-of-the-art solutions to fundamental research problems alongside world-class scientists and engineers across AWS globally. You will work on generative AI (GenAI) topics, contributing to innovations in large language models, generative models for various modalities, and applications that leverage these technologies. You will have the responsibility to design and innovate solutions to benefit our customers, build models to manage large amounts of data, achieve industry-level scalability and efficiency, and rapidly grow and build the team along the way.

BASIC QUALIFICATIONS

– Graduate degree (MS or PhD) in Electrical Engineering, Computer Science, or related disciplines, with strong expertise in machine learning.

– Graduation date between May 2024 and July 2025.

– Publication record in top ML conferences/journals such as NeurIPS, ICML, ICLR, etc.

– Experience in building full-stack machine learning solutions from scratch, including training, debugging, and performance optimization.

– Proficient in Python. Experience with AI/ML frameworks and open-source projects (e.g., PyTorch, TensorFlow) is preferred.

PREFERRED QUALIFICATIONS

– Critical and scientific thinking with the ability to invent, along with a track record of thought leadership and contributions that have advanced the field.

– Strong research acumen. Experience serving as a reviewer for top conferences/journals.

– Experience in GenAI technology, including model training, fine-tuning, and application development for tasks such as RAG, table QA, image QA and multimodal systems

– Experience in engineering scalable, efficient, and highly optimized AI/ML production projects.

– Strong English written and spoken communication skills.

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