Nvidia Senior Responsible AI Architect 

United States, California 

285530436

What you will be doing:

Be an effective leader in crafting and driving adoption of an efficient MLDLC with emphasis on Responsible AI practices and a toolchain, striving to enable engineering teams in delivering innovative, high quality, reusable, reproducible and ethical AI models, datasets, SDKs and AI SW. You will:

• Define and enhance NVIDIA's AI development process and toolchain, for models, datasets, NIMs (NVIDIA Inference Microservices) and SW, to achieve ethical and trustworthy AI products, by specifying required activities, guidelines, templates, metrics, and compliance checklists across model requirements, architecture, training, verification, release, operations, and end-of-life.

• Engage with technical leads, managers, project owners, and security architects of AI teams to identify areas where MLDLC and toolchain can be made more robust, clear, usable, flexible and efficient.

• Prepare and contribute in developing an MLDLC and Responsible AI toolchain roadmap for non-discriminatory, transparent, explainable, safe, robust and secure AI models and SW.

• Craft strategies and automation plans with AI model and dataset teams.

• Influence multiple project teams to embrace and partner in continuous improvement of Responsible AI methods and toolchain.

• Develop and deliver training on MLDLC and tools.

• Gather and address questions, issues, change requests and drive them to closure.

• Drive compliance of MLDLC across teams. Define and achieve key performance metrics.

What we need to see:

• 5+ years recent experience as an ML engineer, data science engineer, or similar with 12+ overall years of professional experience.

• Demonstrated ability in driving the planning and/or execution of engineering life cycle processes, and in releasing commercial products.

• An understanding of the pressures that engineering teams face.

• Experience in evaluating and driving adoption of new life cycle process workflows.

• Master's or PhD degree in Computer Science, Electrical Engineering, or a related field (or equivalent experience).

• Proven experience in machine learning and deep learning algorithm development.

• Strong knowledge of frameworks such as TensorFlow and PyTorch.

Ways to stand out from the crowd:

• Experience in leading medium to largecross-organizational,corporate-wide programs and projects, and in influencing process improvements.

• Background in developing or in leading AI projects from concept to EOL (End of Life).

• Experience in Trustworthy AI or Responsible AI.

• Experience in bringing a novel, never-done-before project to a good end.

• Understanding and hands on experience in Large Language Models, Natural Language Processing, Computer vision, Image Processing, and other generative AI techniques.