Solutions Architect, Open Models

NVIDIA • Santa Clara, CA

1d • $124,000 - $241,500

About The Position

NVIDIA is hiring a Solutions Architect for its AI Software Segment Solutions Architecture team, with a focus on open-weight AI models. The role supports customer-facing technical engagements and connects real-world workloads to NVIDIA’s hardware and software ecosystem. The position is suited to someone who is technically curious, eager to develop deep expertise in NVIDIA platforms, and interested in becoming a trusted technical resource for customers and partners.

Working under the mentorship of senior team members, the Solutions Architect helps customers and partners understand how NVIDIA technologies can address their needs. The role includes participating in scalable architecture design and validation, building and testing solutions, documenting field feedback, and collaborating with engineering and product teams to support successful deployments.

The role also runs end-to-end post-training programs with enterprise customers, including supervised fine-tuning, reinforcement learning (GRPO, DPO, PPO), LoRA / PEFT, data curation, synthetic data generation, reward design, and evaluation design. It builds evaluation environments to measure post-training progress and feed field insights back to Product and Research, and turns hands-on work into reusable recipes, reference pipelines, and playbooks.

Requirements

• Bachelor’s or Master’s degree, or equivalent experience, in Computer Science, Engineering, Mathematics, Physics, Data Science, or a related field.
• 2–5+ years of professional experience in software/hardware engineering, developer relations, technical partnerships, solutions architecture, or a related technical field, with some hands-on exposure to open-weight model customization and the AI/ML systems ecosystem.
• Foundational technical knowledge in AI/ML, particularly post-training, reinforcement learning, LoRA / PEFT, data curation, and evaluation, along with curiosity about developing expertise and contributing to technical solutions.
• Ability to communicate technical concepts clearly to technical and non-technical audiences, with a desire to develop this skill across more complex topics and senior collaborator levels.
• Strong problem-solving skills, intellectual curiosity, and a genuine passion for helping customers succeed with technology.
• Ability to form relationships with customers or partners and interest in developing the technical credibility and trust needed to support complex product decisions.
• 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.
• 3+ years of Linux experience, including comfort launching training and evaluation jobs on SLURM or Kubernetes.

Nice To Haves

• Hands-on technical problem-solving ability and skill in clearly articulating how technology works and applying that understanding to customer challenges.
• Early experience supporting customers and partners in adopting new technologies or platforms, with a passion for enabling others to succeed.
• Experience with and/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 (Nemotron, Qwen, DeepSeek, GLM, Kimi), or applying AI model training to multimodal data.

Responsibilities

• Support technical engagements with customers and partners, helping them understand their workloads and identify how NVIDIA’s technology stack can address their needs under the mentorship of senior team members.
• Participate in the design and validation of scalable architectures, including assisting with integration plans and deployment approaches for customer and partner solutions.
• Build, test, and validate hands-on technical solutions that help customers and partners get started with and scale NVIDIA technologies.
• Document and communicate customer and partner needs and technical feedback, relaying field insights to internal product and engineering teams.
• Collaborate with engineering and product teams to understand NVIDIA’s solutions and support successful customer deployments.
• Run end-to-end post-training programs with enterprise customers, including 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 provide field signal to Product and Research.
• Translate hands-on work into reusable recipes, reference pipelines, and playbooks for NVIDIA teams, customers, and partners.

Benefits

• Equity
• Benefits

What This Job Offers

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