CommunityJobsAdviceEventsReviewsFor EmployersFor ClientsCoach Connect
CommunityJobsAdviceEvents
JOB SEARCH

Manager, LLM Accuracy Evaluation

NVIDIA

2.7

(9)

Multiple Locations (Remote)

#JR1986600

Position summary

a lasting impact on the industry!

What you'll be doing:

  • Lead and mentor a team of highly skilled engineers, fostering their professional growth while solving the most daring problems

  • Drive the accuracy evaluation of flagship models as optimized NVIDIA Inference Microservices (NIM), coordinating efforts across multiple internal teams and external partners to ensure timely and high-quality results.

  • Collaborate with internal customers across the organization, balancing speed and innovation with thorough engineering practices

  • Supervise the development and implementation of new methodologies for evaluating the performance of cutting-edge AI models

  • Build a culture of continuous improvement, encouraging innovation and the adoption of the best software development practices

What we need to see:

  • BS, MS, or PhD in Computer Science, AI, Applied Math, or a related field, or equivalent experience, with 8+ overall years of industry experience, including 3+ years in a leadership or management role.

  • Proven experience leading engineering teams, with a track record of delivering complex AI or deep learning projects on time and within scope.

  • Strong understanding of AI technologies, including NLP, LLMs, and deep learning, with the ability to guide technical decisions and drive innovation.

  • Exceptional communication and interpersonal skills, with the ability to collaborate effectively with internal customers and external partners.

  • Demonstrated ability to mentor and grow engineering talent, fostering a culture of excellence, collaboration, and continuous learning.

Ways to stand out from the crowd:

  • Experience managing teams that have successfully launched AI products or services using LLMs, RAG, or other advanced deep learning models.

  • Demonstrated expertise in deploying and optimizing AI models in production environments, including hands-on experience with platforms like TensorRT, ONNX, or Triton.

  • Strong background in DevOps/MLOps, with a focus on facilitating the deployment and scaling of deep learning models.

  • Proven ability to manage large-scale AI workloads on high-performance computing (HPC) clusters, ensuring efficient resource utilization.

  • Deep understanding of cloud infrastructure, containerization technologies like Docker, and orchestration tools like Kubernetes, with a focus on scalability and reliability.

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.