דרושים Manager Llm Accuracy Evaluation ב-אנבידיה ב-שוויץ

What you’ll be doing:

• Lead and mentor a team of highly skilled engineers, fostering their growth while solving the most ambitious challenges in AI evaluation.

• Drive the accuracy evaluation of flagship AI models, coordinating efforts across internal teams and external partners to ensure timely, high-quality results.

• Collaborate withstakeholders acrossNVIDIA to balance speed of delivery with rigorous engineering practices.

• Develop and implement newmethodologies forevaluating LLMs, multimodal systems, and agent frameworks at scale.

• Build a culture of innovation and excellence, encouraging continuous improvement and adoption of best practices in AI evaluation and deployment.

What we need to see:

• BS, MS, or PhD in Computer Science, AI, Applied Math, or related field, or equivalent experience, with 7+ years of industry experience, including 3+ years in leadership.

• Proven success leading engineering teams anddelivering complexAI/deep learning projects.

• Deep understanding of modern AI technologies—LLMs, multimodal models, retrieval-augmented generation, and agent frameworks—with the ability to guide technical strategy.

• Outstanding communication skills and the ability to partner effectively across organizations and with external collaborators.

• Demonstrated ability to mentor and grow engineering talent, fostering collaboration and technical excellence.

Ways to stand out from the crowd:

• Experience managing teams that shipped AI products or services using LLMs, RAG, or multimodal/agent models.

• Hands-on expertise in deploying and optimizing AI models in production, with platforms such as TensorRT, Triton, or ONNX.

• Strong backgroundin MLOps/DevOps,with a focus on scaling deep learning workloads.

• Proven ability tomanage large-scaleAI evaluations and training workloads on HPC clusters, ensuring efficiency and reproducibility.

• Deep understanding of cloudinfrastructure, containerization(Docker),and orchestration(Kubernetes), with an emphasis on scalability and reliability.

What you will be doing:

• Leading a team of skilled engineers to develop, maintain, and productize real-time calibration software for autonomous and assisted driving systems.

• Driving the evolution of calibration algorithms and infrastructure using large-scale real and synthetic data to ensure performance, robustness, and scalability.

• Guiding architectural decisions and reviewing designs to ensure high performance, modularity, and maintainability of calibration components.

• Coordinating and prioritizing development efforts across areas such as self-calibration, end-of-line calibration, and dev-fleet calibration using multimodal sensor data (LIDAR, Radar, Camera, IMU, etc.).

• Collaborating with other engineering managers, system engineering, safety, and other stakeholders to align on feature development, system integration, and vehicle bring-up plans.

• Ensuring the team follows best practices for software quality, including unit testing, documentation, MISRA/AUTOSAR compliance, and safety-critical development processes.

• Support creation of all necessary work products (documentation, test specification, verification reports, …) to deliver safety-critical software up to ASIL D integrity.

• Guiding root cause analysis and troubleshooting for calibration-related issues in replay and in-car environments.

• Mentoring engineers, fostering technical growth, and supporting career development within your team.

• Reporting status, risks, and milestones to program leadership, and helping shape strategic direction for calibration initiatives.

What we need to see:

• MS or higher in computer science or related engineering discipline (or equivalent experience).

• 8+ overall years of relevant industry experience

• 3+ years experience managing software engineers in the automotive domain.

• Strong C++ and Python programming background with experience in embedded software systems.

• General knowledge of algorithms in Robotics, Estimation, and Computer Vision.

• Demonstrated experience leading software teams with clear ownership of roadmap, quality, and deliverables.

• Excellent communication, organizational, and leadership skills.

• Experience with Git, Linux, and remote collaboration tools in a software development context.

• Understanding of the V model, safety standards, and software product lifecycle, ISO26262 and ASPICE norms.
  

Ways to stand out from the crowd:

• Delivered complex, production-grade software projects in the automotive domain.

• Deep understanding of ADAS and autonomous vehicle systems.

• Prior experience with calibration systems or developing new sensor calibration methods.

• Proven ability to lead distributed teams and work effectively with internal and external partners.