Applied Scientist, Shanghai AI Lab

Key Skills

Aartificial intelligence, Framework, Machine learning techniques, Neural Networks, PyTorch, TensorFlow, UI design, UX design

Job Description

The AWS Shanghai AI Lab is looking for a passionate, talented, and inventive staff 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 of for long-term research projects across domains as machine learning, computer vision, natural language processing, and open-source AI system. Meanwhile, these incubated projects power products across various AWS services.

As part of the lablet, you will take a leadership role and join a vibrant team with a diverse set of expertise in both machine learning and applicational domains. You will work on state-of-the-art solutions on fundamental research problems with other world-class scientists and engineers in AWS around the globe and across the boarders. You will have the responsibility to design and innovate solutions to our customers. You will build models to tame large amount of data, achieve industry-level scalability and efficiency, and along the way rapidly grow and build the team.

BASIC QUALIFICATIONS

• Graduate degree (MS or PhD) in Electrical Engineering, Computer Science or related disciplines. Strong expertise in machine learning.
• Graduated after 2023.6 or to be graduated before 2025.6
• 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. Experiences with AI/ML frameworks and open-source projects (e.g., PyTorch, TensorFlow) are preferred.

PREFERRED QUALIFICATIONS

• Critical and scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.
• Sharp research taste. Experiences serving reviewers for top conferences/journals.
• Experience in engineering practice of scalable, efficient, and highly optimized AI/ML production projects.
• Good English written and spoken communication skills.