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Nvidia Senior Systems Software Engineer TAO Toolkit 
United States, Texas 
566020196

31.07.2024

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:

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

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

  • 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.

You will also be eligible for equity and .