Senior Solutions Architect, Open Models

NVIDIA

. Serve as a trusted advisor by mapping complex customer workloads to NVIDIA’s technology stack .

Posted 11/10/2026full-timeRemote • California • United StatesSenior💰 $184,000 - $356,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates deep technical expertise in AI/ML and open-weight model customization, with a strong ability to design and validate scalable architectures. Proven track record in leading complex customer engagements and mentoring teams while advocating for customer technical needs.

Highest-signal resume keywords

Open-Weight Model CustomizationSupervised Fine-TuningReinforcement LearningDistributed ComputingAI/ML Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringSolutions ArchitectureTechnical PartnershipsData CurationSynthetic Data GenerationReward DesignEvaluation DesignModel Training WorkflowsBenchmark DesignEvaluation Harnesses

Soft Skills

Problem-SolvingIntellectual CuriosityCommunication Skills

Tools & Technologies

NVIDIA TechnologiesSLURMKubernetesClaude CodeCursorCodexNemotronNeMoNeMo-RLNeMo Gym

Industry Keywords

AIMachine LearningCustomer EngagementTechnical DirectionIntegration Achievements

Tech Stack

Tools & technologies

KubernetesNode.js

About the role

Key responsibilities & impact

Serve as a trusted advisor by mapping complex customer workloads to NVIDIA’s technology stack
Co-design scalable architectures with customers and partners, defining technical direction, integration achievements, and deployment plans
Design, validate, and support solutions hands-on
Lead technical engagements and resolve sophisticated customer issues
Advocate for customer technical needs
Partner with engineering and product teams on successful deployment and continuous improvement
Run end-to-end post-training programs, including supervised fine-tuning, reinforcement learning, LoRA / PEFT, data curation, synthetic data generation, reward design, and evaluation design
Build evaluation environments to objectively measure post-training progress
Feed field signals back to Product and Research to improve open-weight models
Build reusable recipes, reference pipelines, and playbooks
Mentor other Solutions Architects and raise the technical bar on reviews and customer-facing deliverables

Requirements

What you’ll need

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 software/hardware engineering, developer relations, technical partnerships, solutions architecture, or product management
3-5+ years of direct, hands-on experience in open-weight model customization
Experience with 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
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
Strong problem-solving skills and intellectual curiosity
Ability to balance customer and partner needs with complex product decisions
Experience leading complex, ambiguous customer engagements
Proficiency with agent-assisted model training workflows and AI agents such as Claude Code, Cursor, or Codex
Expertise in distributed computing, including launching and debugging multi-node training and evaluation jobs on SLURM or Kubernetes
Hands-on technical problem-solving ability
History of enabling customers or partners to adopt NVIDIA technologies and platforms
Experience with and/or contributions to open-source NVIDIA AI libraries and models, particularly Nemotron, NeMo, NeMo-RL, and NeMo Gym
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 training AI models on multimodal data
Experience designing benchmarks and evaluation harnesses adopted by other teams

Benefits

Comp & perks

Highly competitive salaries
Comprehensive benefits package
Equity