NVIDIA
Senior Responsible AI Engineer
Job Description
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by a great technology—and amazing people.
Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAn, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We’re looking for a Senior Responsible AI Engineer to join our Infrastructure, Planning and Processes organization. In this role, you will evaluate, refine, develop, test and automate groundbreaking AI research, practices and tools that augment and enhance our Machine Learning (ML) Development Life Cycle (MLDLC) process for ensuring ethically responsible AI models, datasets and SW, and then release and support the toolchain to all ML and DL (Deep Learning) NVIDIA projects, across thousands of engineers!
What you will be doing:
As the Responsible AI Toolchain Engineer, you will be a key contributor in shaping NVIDIA’s contribution to ethical development of AI models and SW!
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Identify open source, 3rd party, academic or internal software tools that aim to determine, evaluate, analyze, and report on performance of an AI model or dataset along the Responsible AI vectors of non-discrimination, privacy, security, safety, transparency, explainability, and more.
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Develop clear decision criteria for evaluating Responsible AI research, methods and tools.
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Evaluate the value and capabilities of the software practices and tools against clearly defined decision criteria.
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Test identified software tools and approaches on NVIDIA’s AI models, datasets and AI SW, report on relative value of each tool or method, and make recommendations whether to incorporate into NVIDIA’s MLDLC.
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Contribute to open source software tool projects involved in Responsible AI.
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Make an automation proposal for an end-to-end Responsible AI toolchain, and execute to success, as measured by productivity improvement of NVIDIA’s AI model development process.
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Influence engineering teams to embrace and partner in continuous improvement of MLDLC toolchain and process for Responsible AI.
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Develop and deliver training on MLDLC Responsible AI toolchain, and partner with engineering teams to continuously improve the Responsible AI tool chain.
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Regularly communicate the program status and key issues to management.
What we need to see:
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Bachelor’s, Master’s, or PhD in Computer Science, Computer Architecture, Electrical Engineering, Intelligent Systems, Machine Learning, Data Science, or a relevant field.
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5+ years of experience in development of software, tools or automation frameworks.
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Prior experience in programming skills or knowledge in Python, C, C++,
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Experience in one or more of: PyTorch, PERL, GitHub, SHAP, MLOps systems, or projects in the space of ethical AI tools or open source projects.
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Familiarity in one or more of: Sklearn, Pandas, Numpy, Jupyter, Slurm
Ways to stand out from the crowd:
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Experience on AI dataset projects, including data collection, labeling, and verification.
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Experience on AI model training or inference projects.
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Any prior internship experience on tools for ensuring Responsible AI.
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Experience in Computer Vision, Hugging Face transformers, Fine Tuning LLMs and Multi-GPU Training
NVIDIA is widely considered to be one of the technology world’s most desirable employers.
NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family at www.nvidiabenefits.com/. 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 andfuture 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.
