Nvidia Senior Systems Software Engineer TAO Toolkit 

United States, California 

235709497

What you’ll be doing:

• Build advanced tools to evaluate our AI models on multiple parameters including bias, risk, safety, and regulatory compliance.

• Stay updated with the latest advancements in Trustworthy AI research and integrate relevant findings into our AI systems.

• Design and implement governance frameworks for tracking and being responsible for the lifecycle of AI models, ensuring adherence to best practices and standards.

• Create and refine algorithms to detect and mitigate bias in AI models, ensuring fairness and ethical decision-making.

• Develop robust safety measures and protocols to ensure AI models operate reliably and securely in diverse environments.

• Ensure AI systems meet all regulatory requirements and standards, maintaining compliance with industry and legal guidelines.

• Work closely with data scientists, engineers, and product managers to integrate AI trust and safety measures seamlessly into our products.

What we need to see:

• 5+ years of proven experience working on problems of moderate scope where analysis of situations or data requires a review of a variety of factors.

• MS or PhD in Computer Science, Data Science, AI, or a related field (or equivalent experience).

• Strong programming and debugging skills with proficiency in Python, Bash, or similar scripting languages.

• Experience with deep learning frameworks such as TensorFlow, PyTorch, or others.

• Proficiency with containerization technologies like Docker and orchestration tools like Kubernetes.

• Publications in top-tier conferences or contributions to significant open-source projects in the field of AI.

• Excellent communication and collaboration abilities to work optimally in a cross-functional team environment.

• Strong analytical and problem-solving skills with a focus on practical and scalable AI solutions.

Ways to stand out from the crowd:

• Validated experience in building tools for AI model assessment and governance.

• Awareness of ethical issues in AI and a commitment to developing fair and responsible AI technologies.