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NVIDIA
NVIDIA
H1B Visa SponsorArtificial IntelligenceHealthcareManufacturing
NVIDIA develops accelerated computing and artificial intelligence technologies used across gaming, data centers, cloud computing, healthcare, manufacturing, automotive, and robotics. Its work spans graphics processing units, AI platforms, simulation, and industry-focused solutions, including NVIDIA Omniverse for collaborative 3D workflows, NVIDIA DRIVE for autonomous vehicle development, and NVIDIA Clara for healthcare applications. The company brings together large technical teams working on the infrastructure and software that support advanced computing, simulation, and AI-driven analytics.
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Senior Architect, Coding Model Performance and Post-Training at NVIDIA (Remote, US)

Lead performance evaluation and post-training for NVIDIA’s AI models for code generation and software engineering. Develop benchmarks, reward strategies, and scalable training infrastructure.

USUnited StatesCACaliforniaCOColorado
$224,000 – $431,250 / year
RemoteFull-timeSeniorEnglish RequiredArchitect
Python

Description

  • Create frameworks to evaluate coding models across code 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 behavior to identify improvement opportunities.
  • Improve performance on complex coding tasks through targeted training, reward design, curriculum development, and iterative error analysis.
  • Build scalable, reproducible infrastructure for training experiments, evaluation pipelines, and performance analysis.
  • Work with research scientists, infrastructure engineers, and product teams to turn model insights into production capabilities.

Requirements

  • Bachelor’s degree or equivalent experience in computer science or AI.
  • At least 12 years of relevant work experience.
  • Strong Python programming skills.
  • Strong knowledge of large language models, transformer architectures, and generative model training and evaluation.
  • Foundational knowledge of reinforcement learning algorithms and implementation, including MDPs, policies, and reward design.
  • Deep knowledge of software engineering fundamentals, code generation, automated testing, and program correctness.
  • A record of leading model development lifecycles, including dataset versioning, experiment tracking, and evaluation pipelines.
  • Experience training or post-training state-of-the-art coding models or models for software engineering agents.
  • Experience with execution-based and verifiable rewards, reward hacking mitigation, and automated code evaluation.
  • Familiarity with coding benchmarks and evaluation environments such as SWE-bench.

Benefits

  • Competitive salary.
  • Comprehensive benefits package.
  • Equity.
  • Benefits for employees and their families.

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