Senior Responsible AI Architect

Posted 2 Days Ago
Be an Early Applicant
Santa Clara, CA
Senior level
Artificial Intelligence • Hardware • Robotics • Software • Metaverse
The Role
As a Senior Responsible AI Architect at NVIDIA, you will lead the adoption of a responsible AI development process and toolchain, focusing on ethical AI practices. Your responsibilities include defining the AI development framework, engaging with technical teams, crafting automation strategies, and ensuring compliance across various AI projects, ultimately driving innovation in AI technologies.
Summary Generated by Built In

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.

NVIDIA is looking for an expert Senior Responsible AI Architect to join its Infrastructure, Planning and Processes organization, with creativity and passion to take NVIDIA's lead in AI to the next level! In this role, you will deliver cross-organizational impact by defining, enhancing, championing, rolling out and supporting a Responsible AI focused Machine Learning (ML) Development Life Cycle (MLDLC) process and toolchain, which will be applied by thousands of engineers on all ML and DL (Deep Learning) NVIDIA projects, ranging from LLM (Large Language Models) foundational models, Computer Vision (CV), Speech, Automotive, Robotics to Biology.

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 large cross-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.

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/. It’s a unique legacy of innovation that’s fueled by a great technology—and amazing people.

The base salary range is 220,000 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.

Top Skills

Deep Learning
Machine Learning
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

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.”

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