Senior Solutions Architect, Open Models

NVIDIA • Santa Clara, CA

1d • $184,000 - $356,500

About The Position

NVIDIA is hiring a Senior Solutions Architect for its AI Software Segment Solutions Architecture team, focused on open-weight AI models. The role drives technical engagement with customers and partners, connecting real-world workloads to NVIDIA’s open-weight model and software ecosystem and helping developers and enterprises adopt and scale NVIDIA platforms. The architect serves as a trusted technical advisor, maps complex workloads to NVIDIA technologies, and helps customers and partners achieve measurable outcomes.

The role involves co-designing scalable architectures, defining technical direction and deployment plans, and providing hands-on design, validation, and support. It leads complex technical engagements and partners with engineering and product teams to support successful deployments and continuous improvement.

A key focus is running end-to-end enterprise post-training programs, including supervised fine-tuning, reinforcement learning, LoRA / PEFT, data curation, synthetic data generation, reward design, and evaluation design. The architect builds objective evaluation environments that inform customers’ progress and provide field feedback to Product and Research. The role also scales impact through reusable recipes, reference pipelines, and playbooks, while mentoring other Solutions Architects and raising the technical bar for reviews and customer-facing deliverables.

Requirements

• Bachelor’s or Master’s degree, or equivalent experience, in Computer Science, Engineering, Mathematics, Physics, Data Science, or a related field.
• 8+ years of professional experience in industry across software or hardware engineering, developer relations, technical partnerships, solutions architecture, or product management.
• 3–5+ years of direct, hands-on experience in open-weight model customization, including supervised fine-tuning, reinforcement learning (GRPO, DPO, PPO), LoRA / PEFT, data curation, synthetic data generation, reward design, and evaluation design.
• Deep technical expertise in AI/ML and open-weight model post-training, with a track record of driving customer engagements and contributing to software platforms, systems, and libraries.
• Ability to communicate sophisticated technical ideas clearly to technical and non-technical audiences, from engineers to C-level executives.
• Strong problem-solving skills, intellectual curiosity, and dedication to helping customers succeed.
• Proven ability to balance customer and partner needs with driving complex product decisions through positive relationships.
• Experience leading complex, ambiguous customer engagements and proactively moving them forward.
• Proficiency with agent-assisted model training workflows and comfort using AI agents such as Claude Code, Cursor, or Codex to build, debug, and iterate on training and evaluation pipelines.
• Expertise in distributed computing, including launching and debugging multi-node training and evaluation jobs on SLURM or Kubernetes.

Nice To Haves

• Hands-on technical expertise and ability to clearly describe solution paths for complex challenges.
• History of enabling customers or partners to optimally adopt NVIDIA technologies and platforms.
• Technical vision that influences research, product, and engineering decisions and drives production outcomes.
• Experience with or contributions to open-source NVIDIA AI libraries and models, particularly Nemotron, NeMo, NeMo-RL, and NeMo Gym.
• Hands-on experience designing agent environments, synthetic data pipelines, and verifiable rewards for RL post-training, or using serverless post-training APIs such as Tinker.
• Hands-on experience customizing open-weight models such as Nemotron, Qwen, DeepSeek, GLM, or Kimi, or experience with AI model training applied to multimodal data.
• Experience designing benchmarks and evaluation harnesses adopted by other teams.

Responsibilities

• Serve as a trusted advisor by understanding complex or large-scale customer workloads and mapping them to NVIDIA’s technology stack to achieve measurable outcomes.
• Co-design advanced, scalable architectures with customers and partners, defining technical direction, integration achievements, and deployment plans.
• Design, validate, and support solutions through hands-on technical engagement.
• Lead technical engagements, help customers resolve sophisticated issues, and advocate for their technical needs.
• Partner with engineering and product teams to enable successful deployment and continuous improvement of NVIDIA solutions.
• Run end-to-end enterprise post-training programs involving supervised fine-tuning, reinforcement learning (GRPO, DPO, PPO), LoRA / PEFT, data curation, synthetic data generation, reward design, and evaluation design.
• Build evaluation environments that objectively measure post-training progress and feed field signals back to Product and Research.
• Build reusable recipes, reference pipelines, and playbooks to help other teams succeed.
• Mentor other Solutions Architects and raise the technical bar for reviews and customer-facing deliverables.

Benefits

• Highly competitive salaries
• Comprehensive benefits package
• Equity

What This Job Offers

• Job Type: Full-time
• Career Level: Senior