2 days ago
USA (city not specified) or Santa Clara, CA, USAMid Level / Senior
H1B sponsor
Base Salary
$124k - $242k/yr
Responsibilities
- Support customer and partner technical engagements by understanding workloads and mapping them to NVIDIA technologies.
- Participate in designing and validating scalable architectures, integration plans, and deployment approaches.
- Build, test, and validate hands-on solutions for adopting and scaling NVIDIA technologies.
- Document customer and partner needs and relay technical feedback to product and engineering teams.
- Collaborate with engineering and product teams to support successful customer deployments.
- Run enterprise post-training programs involving supervised fine-tuning, reinforcement learning, LoRA/PEFT, data curation, synthetic data generation, reward design, and evaluation design.
- Build evaluation environments that measure post-training progress and provide field feedback to Product and Research.
- Create reusable recipes, reference pipelines, and playbooks for post-training and evaluation workflows.
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 or hardware engineering, developer relations, technical partnerships, solutions architecture, or a related technical field.
- Hands-on exposure to open-weight model customization and the AI/ML systems ecosystem.
- Foundational knowledge of post-training, reinforcement learning, LoRA/PEFT, data curation, and evaluation.
- Ability to communicate technical concepts to technical and non-technical audiences and build customer or partner relationships.
- Proficiency with agent-assisted model training workflows using tools such as Claude Code, Cursor, or Codex.
- At least 3 years of Linux experience, including launching training and evaluation jobs on SLURM or Kubernetes.
- Preferred experience with NVIDIA AI libraries and models, including Nemotron, NeMo, NeMo-RL, and NeMo Gym.
- Preferred experience designing agent environments, synthetic data pipelines, verifiable rewards, serverless post-training workflows, or customizing models such as Nemotron, Qwen, DeepSeek, GLM, and Kimi.
Benefits
- Eligible for equity and benefits.
- Applications will be accepted at least until November 14, 2026.
- Base salary varies by location, experience, and other objective job-related factors.
Tech Stack
Categories
Solutions Engineering
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.