1 day ago
Base Salary
$224k - $431k/yr
Responsibilities
- Develop frameworks to measure and analyze coding-model performance across generation, debugging, completion, repository reasoning, and multi-step software-engineering tasks.
- Develop and optimize post-training pipelines using supervised fine-tuning, preference optimization, reinforcement learning, and outcome- or process-based reward modeling.
- Analyze benchmark results, training dynamics, failure modes, and model behaviors to identify improvement opportunities.
- Improve coding-model performance through training interventions, reward design, curriculum development, and iterative error analysis.
- Build scalable, reproducible infrastructure for training experiments, evaluation pipelines, and model-performance analysis.
- Collaborate with research scientists, infrastructure engineers, and product teams to deliver production-ready capabilities.
Requirements
- Bachelor’s degree or equivalent experience in Computer Science or AI and 12+ years of meaningful work experience.
- Excellent Python programming skills and strong understanding of large language models, transformer architectures, and generative-model training and evaluation.
- Foundational understanding of reinforcement-learning algorithms and implementation, including MDPs, policies, and reward design.
- Deep understanding of software-engineering fundamentals, code generation, automated testing, and program correctness.
- Proven ability to lead model-development lifecycles involving dataset versioning, experiment tracking, and evaluation pipelines.
- Preferred: experience training or post-training state-of-the-art coding models or models for software-engineering agents.
- Preferred: experience with execution-based rewards, verifiable rewards, reward-hacking mitigation, and automated code evaluation.
- Preferred: familiarity with coding benchmarks and evaluation environments such as SWE-bench.
Benefits
- NVIDIA offers comprehensive benefits and equity.
- Base salary is determined by location, experience, and pay for similar positions.
- Applications will be accepted at least until October 17, 2026.
- This posting is for an existing vacancy.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.