NVIDIA

NVIDIA is at the forefront of powering AI and LLMs across multiple industries. Our thesis is that to build exceptional LLMs you need exceptional human beings to train them. Humans are essential in providing the best training data for these models, and NVIDIA operates the largest network of humans in the world to provide this training data. As the Head of Data Quality Operations, you will be responsible for ensuring that our training data quality is as useful for customers as possible. You will own ideating what high-quality training means and looks like across various projects, driving thought leadership with our customers about data quality, developing the entire annotator training program, creating our “golden datasets” to programmatically evaluate annotators, and more. The role involves a combination of critical thinking, data analysis, roll-up-your-sleeves operations, and cross-functional collaboration. This is one of the highest-impact roles at the company. The ideal candidate has a strong entrepreneurial demeanor, is comfortable leading a team and working with them under ambiguity at a high velocity and can make things happen.

What you'll be doing:

• Work with linguists, annotators, academics, and researchers to ensure NVIDIA stays at the forefront of the definition of data quality.
• Own communication and thought leadership around data quality with key customers and collaborators.
• Supervise the training materials and curriculum for our entire annotator base.
• Supervise the creation of our “golden datasets” to ensure we have a quality signal on our annotators in a scalable way.
• Work with project teams to understand the nuances and challenges of developing good training data, come up with perspectives on how those edge cases should be handled, and relay that perspective to our customers.
• Create and scale a data innovation team to use pioneering methods to ensure annotation quality and increase data value.
• Key Collaborator in planning/design/implementation and testing of annotation tooling.
• Lead a global workforce of over a thousand annotators including a data science team, and a quality assurance team.

What we need to see:

• PhD. Degree or equivalent experience with focus on applied machine learning.
• 7+ years of overall experience with 4+ years of experience in Management/leadership roles.
• Strong communication skills.

Ways to stand out from the crowd:

• 3 years of demonstrated ability with LLMs.
• Experience in creating datasets from scratch and repurposing/reannotating.
• Excited to solve ambiguous problems.
• A relentless attitude of testing and iterating.

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence. NVIDIA offers highly competitive salaries and a comprehensive benefits package.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you are creative, results-oriented and enjoy having fun, then what are you waiting for? Apply today!

The base salary range is 216,000 USD - 345,000 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.