NVIDIA is hiring a Systems Software Engineer to join the TAO Toolkit engineering team. Our team crafts building blocks to make AI easy to develop, integrate, and deploy. As a dedicated member, you will help advance our Trustworthy AI efforts by building and maintaining the infrastructure, tools, and processes vital to support the machine learning model lifecycle, ensuring the fairness, safety, and compliance of our AI systems. If you have a passion for innovative technologies and a commitment to developing responsible and ethical AI, we invite you to join our diverse team at NVIDIA.
TAO Toolkit | NVIDIA Developer | https://developer.nvidia.com/tao-toolkit
What you’ll be doing:
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Build advanced tools to evaluate our AI models on multiple parameters including bias, risk, safety, and regulatory compliance.
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Design, implement, and maintain an efficient and scalable CI/CD platform that would enable model versioning, packaging, and integration with existing systems.
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Stay updated with the latest advancements in Trustworthy AI research and integrate relevant findings into our AI systems.
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Develop and establish governance frameworks for tracking and being responsible for the lifecycle of AI models, ensuring adherence to best practices and standards.
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Create and refine algorithms to detect and mitigate bias in AI models, ensuring fairness and ethical decision-making.
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Develop robust safety measures and protocols to ensure AI models operate reliably and securely in diverse environments.
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Ensure AI systems meet all regulatory requirements and standards, maintaining compliance with industry and legal guidelines.
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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:
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MS or PhD in Computer Science, Data Science, AI, or a related field (or equivalent experience).
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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.
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Strong programming and debugging skills with proficiency in Python, Bash, or similar scripting languages.
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Experience with deep learning frameworks such as TensorFlow, PyTorch, or others.
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Proficiency with containerization technologies like Docker and orchestration tools like Kubernetes.
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Publications in top-tier conferences or contributions to significant open-source projects in the field of AI.
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Excellent communication and collaboration abilities to work optimally in a cross-functional team environment.
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Strong analytical and problem-solving skills with a focus on practical and scalable AI solutions.
Ways to stand out from the crowd:
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Proven experience in building tools for AI model assessment and governance.
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Awareness of ethical issues in AI and a commitment to developing fair and responsible AI technologies.
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and versatile people in the world working with us and our engineering teams are growing fast in some of the most impactful fields of our generation: Deep Learning, Artificial Intelligence, and Autonomous Vehicles. If you're a tools-driven engineer who enjoys autonomy and shares our passion for technology, we want to hear from you.
The base salary range is 148,000 USD - 339,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
